Workshop

NeurIPS 2024 Workshop: Machine Learning and the Physical Sciences

Siddharth Mishra-Sharma · Nicole Hartman · Vinicius Mikuni · Mariel Pettee · Sebastian Wagner-Carena · Antoine Wehenkel · Kyle Cranmer · Savannah Thais · Benjamin Nachman · Brian Nord

Project Page [ OpenReview]

Abstract

Physical sciences and machine learning: more than the sum of their parts. Join us to discuss research at the convergence of these fields!

Video

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Schedule

Timezone: America/Los_Angeles

8:15 AM

Opening remarks Opening remarks

Video

8:30 AM

Invited talk: data-driven vs inductive bias-driven methods in machine learning and the physical sciences Invited talk

Lukas Heinrich

Video

9:00 AM

Panel: data-driven vs inductive bias-driven methods in machine learning and the physical sciences Invited panel

Animashree Anandkumar · Naoya Takeishi · Johannes Brandstetter

Video

10:00 AM

Coffee break

10:30 AM

Invited talk: Pushing the limits of real-time ML: Nanosecond inference for Physics Discovery at the LHC Invited talk

Thea Klaeboe Aarrestad

Video

11:00 AM

Poster session 1 Poster session

12:15 PM

Lunch break

1:15 PM

Contributed talk: Joint cosmological parameter inference and initial condition reconstruction with Stochastic Interpolants Contributed talk

Carolina Cuesta

Video

1:30 PM

Large language models & quantum many-body physics: a case study Invited talk

Yasaman Bahri

Video

2:00 PM

Invited talk: Valid scientific inference with neural density estimators and generative models Invited talk

Ann Lee

Video

2:30 PM

Contributed talk: Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle Physics Contributed talk

Annalena Kofler

Video

2:45 PM

Contributed talk: Robust Emulator for Compressible Navier-Stokes using Equivariant Geometric Convolutions Contributed talk

Wilson G. Gregory

Video

3:00 PM

Coffee break Coffee break

3:30 PM

Contributed talk: The State of Julia for Scientific Machine Learning Contributed talk

Edward Berman

Video

3:45 PM

Data-Driven High-Dimensional Inverse Problems: A Journey Through Strong Gravitational Lensing Data Analysis Invited talk

Laurence Perreault-Levasseur

Video

4:15 PM

Poster session 2 Poster session

5:25 PM

Closing remarks Closing remarks

Video

Neural Networks for Dissipative Physics Using Morse-Feshbach Lagrangian Poster

Veera Sundararaghavan · Jeff Simmons · Megna Shah

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OrbNet-Spin: Quantum Mechanics Informed Geometric Deep Learning For Open-shell Systems Poster

Beom Seok Kang · Amin Tavakoli · Vignesh Bhethanabotla · William Goddard · Animashree Anandkumar

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Enhancing Molecular Expressiveness through Multi-View Representations Poster

Indra Priyadarsini S · Seiji Takeda · Lisa Hamada · Hajime Shinohara

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Learning Conformal Field Theory with Symbolic Regression: Recovering the Symbolic Expressions for the Energy Spectrum Poster

Haotian Cao · Garrett Merz · Kyle Cranmer · Gary Shiu

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Physics-informed reduced order model with conditional neural fields Poster

Minji Kim · Tianshu Wen · Kookjin Lee · Youngsoo Choi

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Learning the Evolution of Physical Structure of Galaxies via Diffusion Models Poster

Andrew Lizarraga · Eric Jiang · Jacob Nowack · Yunqi Li · Ying Nian Wu · Bernie Boscoe · Tuan Do

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Simulation-based inference with scattering representations: scattering is all you need Poster

Kiyam Lin · Benjamin Joachimi · Jason McEwen

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A Platform, Dataset, and Challenge for Uncertainty-Aware Machine Learning Poster

David Rousseau · Wahid Bhimji · Ragansu Chakkappai · Steven Farrell · Aishik Ghosh · Isabelle Guyon · Chris Harris · Elham E Khoda · Benjamin Nachman · Ihsan Ullah · Sascha Diefenbacher · Yuan-Tang Chou · Paolo Calafiura · Yulei Zheng · Jordan Dudley

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Scalable physics-guided data-driven component model reduction for steady Navier-Stokes flow Poster

Seung Whan Chung · Youngsoo Choi · Pratanu Roy · Thomas Roy · Tiras Y. Lin · Du Nguyen · Christopher Hahn · Eric Duoss · Sarah Baker

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Domain-Adaptive ML for Surface Roughness Predictions in Nuclear Fusion Poster

Shashank Galla · Antonios Alexos · Jay Yoo · Junze Liu · Kshitij Bhardwaj · Sean Hayes · Monika Biener · Pierre Baldi · Satish Bukkapatnam · Suhas Bhandarkar

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3D-PDR Orion dataset and NeuralPDR: Neural Ordinary Equations for Photodissociation regions Poster

Gijs Vermariën · Serena Viti · Rahul Ravichandran · Thomas Bisbas

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Tomographic SAR Reconstruction for Forest Height Estimation Poster

Grace Colverd · Jumpei Takami · Laura Schade · Karol Bot · Joseph Alejandro Gallego Mejia

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Similarity-Aware Relative Difference Learning for Improved Molecular Activity Prediction Poster

Karina Zadorozhny · Kangway Chuang · Bharath Sathappan · Ewan Wallace · Vishnu Sresht · Colin Grambow

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Neural network prediction of strong lensing systems with domain adaptation and uncertainty quantification Poster

Shrihan Agarwal · Aleksandra Ciprijanovic · Brian Nord

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Domain adaptation in application to gravitational lens finding Poster

Hanna Parul · Michael Toomey · Pranath Reddy Kumbam · Sergei Gleyzer

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Hybrid Summary Statistics Poster

Lucas Makinen · Ce Sui · Benjamin Wandelt

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The State of Julia for Scientific Machine Learning Poster

Edward Berman · Jacob Ginesin

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PCN: a deep learning approach to jet tagging utilizing novel graph construction methods and Chebyshev graph convolutions Poster

Mihir Relan · Yash Semlani · Krithik Ramesh

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Reinforcement Learning for Control of Non-Markovian Cellular Population Dynamics Poster

Josiah Kratz · Jacob Adamczyk

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Domain Adaptation of Drag Reduction Policy to Partial Measurements Poster

Anton Plaksin · Georgios Rigas

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Efficient Generation of Molecular Clusters with Dual-Scale Equivariant Flow Matching Poster

Akshay Subramanian · Shuhui Qu · Cheol Woo Park · Sulin Liu · Janghwan Lee · Rafael Gomez-Bombarelli

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Learning functional forms of fragmentation functions for hadron production using symbolic regression Poster

Nour Makke · Sanjay Chawla

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Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks Poster

Nikhil Garuda · John Wu · Dylan Nelson · Annalisa Pillepich

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DiffLense: A Conditional Diffusion Model for Super-Resolution of Gravitational Lensing Data Poster

Pranath Reddy Kumbam · Michael Toomey · Hanna Parul · Sergei Gleyzer

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Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle Physics Poster

Annalena Kofler · Vincent Stimper · Mikhail Mikhasenko · Michael Kagan · Lukas Heinrich

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Reconstruction of Continuous Cosmological Fields from Discrete Tracers with Graph Neural Networks Poster

Yurii Kvasiuk · Jordan Krywonos · Matthew Johnson · Moritz Münchmeyer

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Virtual Reality for Understanding Artificial-Intelligence-driven Scientific Discovery with an Application in Quantum Optics Poster

Philipp Schmidt · Carlos Ruiz-Gonzalez · Sören Arlt · Xuemei Gu · Carla Rodríguez · Mario Krenn

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Neural Entropy Poster

Akhil Premkumar

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Robust one-shot spectroscopic multi-component gas mixture detection via randomized smoothing Poster

Mohamed Sy · Emad Al Ibrahim · Aamir Farooq

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Galaxy Dust Maps with Conditional Score Models Poster

Jared Siegel · Peter Melchior

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Data-Driven Reweighting for Monte Carlo Simulations Poster

Ahmed Youssef · Christian Bierlich · Philip Ilten · Tony Menzo · Stephen Mrenna · Manuel Szewc · Michael K. Wilkinson · Jure Zupan

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Improving Flow Matching for Simulation-Based Inference Poster

Janis Fluri · Thomas Hofmann

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Equation-driven Neural Networks for Periodic Quantum Systems Poster

Circe Hsu · Marios Mattheakis · Gabriel Schleder · Daniel Larson

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Galaxy Morphology Classification with Counterfactual Explanation Poster

Zhuo Cao · Lena Krieger · Hanno Scharr · Ira Assent

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AP-SVM: Unsupervised Data Cleaning for the LEGEND Experiment Poster

Esteban León · Julieta Gruszko · Aobo Li · Brady Bos · M.A. Schott · John Wilkerson · Reyco Henning · Matthew Busch · Eric Martin · Guadalupe Duran · Jason Chapman

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Learning Physics From Video: Unsupervised Physical Parameter Estimation for Dynamical Systems Poster

Alejandro Garcia · Jan van Gemert · Daan Brinks · Nergis Tomen

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Towards a Reinforcement Learning framework for purely online 3D-molecular structure discovery Poster

Bjarke Hastrup · François Cornet · Tejs Vegge · Arghya Bhowmik

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A perspective on symbolic machine learning in physical sciences Poster

Nour Makke · Sanjay Chawla

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Semi-supervised Super-resolution for Gravitational Lenses with Estimated Degradation Model Poster

Peimeng Guan · Michael Toomey · Sergei Gleyzer

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Exact and approximate error bounds for physics-informed neural networks Poster

Augusto Chantada · Pavlos Protopapas · Luca Gomez Bachar · Susana Landau · Claudia Scóccola

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AI Meets Antimatter: Unveiling Antihydrogen Annihilations Poster

Ashley Ferreira · Mahip Singh · Andrea Capra · Ina Carli · Daniel Quiceno · Wojciech Fedorko · Makoto Fujiwara · Muyan Li · Lars Martin · Yukiya Saito · Gareth Smith · Anqi Xu

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S-KANformer: Enhancing Transformers for Symbolic Calculations in High Energy Physics Poster

Ritesh Bhalerao · Eric Reinhardt · Sergei Gleyzer · Nobuchika Okada · Victor Baules

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Uncertainty Quantification for Martian Surface Spectral Analysis using Bayesian Deep Learning Poster

Mark Hinds · Michael Geyer · Natalie Klein

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Reconstructing Quasar Spectra and Measuring the Ly$\alpha$ Forest with {\sc SpenderQ} Poster

ChangHoon Hahn · Satya Gontcho A Gontcho · Peter Melchior

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Neural Posterior Unfolding Poster

Jingjing Pan · Benjamin Nachman · Vinicius Mikuni · Jay Chan · Krish Desai · Fernando Torales Acosta

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Harnessing Loss Decomposition for Long-Horizon Wave Predictions via Deep Neural Networks Poster

Indu Kant Deo · Rajeev Jaiman

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D3PU: Denoising Diffusion Detector Probabilistic Unfolding in High-Energy Physics Poster

Camila Pazos · Shuchin Aeron · Pierre-Hugues Beauchemin · Vincent Croft · Martin Klassen · Taritree Wongjirad

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Digital Discovery of interferometric Gravitational Wave Detectors Poster

Mario Krenn · Yehonathan Drori · Rana Adhikari

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Training Hamiltonian neural networks without backpropagation Poster

Atamert Rahma · Chinmay Datar · Felix Dietrich

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Using Variational Autoencoding to Infer the Masses of Exoplanets Embedded in the Disks of Gas and Dust Orbiting Young Stars Poster

Sayed Mahmud · Ramit Dey · Sayantan Auddy · Neal Turner · Jeffrey Bary

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Machine Learning for Reparameterization of Multi-scale Closures Poster

Hilary Egan · peter ciecielski · hariswaram sitaraman · megan crowley

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Learning Symmetry-Independent Jet Representations via Jet-Based Joint Embedding Predictive Architecture Poster

Subash Katel · Haoyang Li · Zihan Zhao · Javier Duarte

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Super-Resolution without High-Resolution label for Black Hole Simulations Poster

Thomas Helfer · Thomas Edwards · Jessica Dafflon · Kaze W. K. Wong · Matthew Olson

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Accelerated Bayesian parameter estimation and model selection for gravitational waves with normalizing flows Poster

Alicja Polanska · Thibeau Wouters · Peter Pang · Kaze W. K. Wong · Jason McEwen

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Machine learned reconstruction of tsunami waves from sparse observations Poster

Edward McDugald · Darren Engwirda · Arvind Mohan · Agnese Marcato · Javier E. Santos

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Robust Emulator for Compressible Navier-Stokes using Equivariant Geometric Convolutions Poster

Wilson G. Gregory · David W Hogg · Kaze W. K. Wong · Soledad Villar

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BNEM: A Boltzmann Sampler Based on Bootstrapped Noised Energy Matching Poster

RuiKang OuYang · Bo Qiang · José Miguel Hernández-Lobato

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PhysBERT: A Text Embedding Model for Physics Scientific Literature Poster

Thorsten Hellert · Andrea Pollastro · João Montenegro

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Enhancing Cosmological Simulations with Efficient and Interpretable Machine Learning in the Gabor Wavelet Basis Poster

Cooper Jacobus · Leander Thiele · Peter Harrington · Jia Liu · Zarija Lukić

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Diffusion models for lattice gauge field simulations Poster

Qianteng Zhu · Gert Aarts · Wei Wang · Kai Zhou · Lingxiao Wang

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3D Cloud reconstruction through geospatially-aware Masked Autoencoders Poster

Stella Girtsou · Emiliano Diaz · Lilli Freischem · Joppe Massant · Kyriaki-Margarita Bintsi · Giuseppe Castiglione · William Jones · Michael Eisinger · J. Emmanuel Johnson · Anna Jungbluth

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Uncertainty quantification for fast reconstruction methods using augmented equivariant bootstrap: Application to radio interferometry Poster

Mostafa Cherif · Tobías I. Liaudat · Jonathan Kern · Christophe Kervazo · Bobin

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GFlowNets for Hamiltonian decomposition in groups of compatible operators Poster

Rodrigo Vargas-Hernandez · Isaac L. Huidobro-Meezs · Dai · Guillaume Rabusseau

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Harnessing Machine Learning for Single-Shot Measurement of Free Electron Laser Pulse Power Poster

Till Korten · Vladimir Rybnikov · Mathias Vogt · Juliane Roensch-Schulenburg · Peter Steinbach · Najmeh Mirian

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Discovering How Ice Crystals Grow Using NODE's and Symbolic Regression Poster

Kara Lamb · Jerry Harrington

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Loss function to optimise signal significance in particle physics Poster

Jai Bardhan · Cyrin Neeraj · Subhadip Mitra · Tanumoy Mandal

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Sharing Space: A Survey-agnostic Variational Autoencoder for Supernova Science Poster

Kaylee de Soto · Ana Sofia Uzsoy · V Villar

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Two-Stage Coefficient Estimation in Symbolic Regression for Scientific Discovery Poster

Masahiro Negishi · Yoshitomo Matsubara · Naoya Chiba · Ryo Igarashi · Yoshitaka Ushiku

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Transforming Simulation to Data Without Pairing Poster

Eli Gendreau-Distler · Luc Le Pottier · Haichen Wang

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Correcting misspecified score-based priors for inverse problems: An application to strong gravitational lensing Poster

Gabriel Missael Barco · Alexandre Adam · Connor Stone · Yashar Hezaveh · Laurence Perreault-Levasseur

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Joint cosmological parameter inference and initial condition reconstruction with Stochastic Interpolants Poster

Carolina Cuesta · Adrian Bayer · Michael Albergo · Siddharth Mishra-Sharma · Chirag Modi · Daniel Eisenstein

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Reconstructing dissipative dynamical systems from spatially and temporally sparse sensors Poster

Alex Guo · Galen Craven · Javier E. Santos · Charles Young

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GraphNeT 2.0 - A Deep Learning Library for Neutrino Telescopes Poster

Rasmus Ørsøe · Aske Rosted

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Data-Driven, Parameterized Reduced-order Models for Predicting Distortion in Metal 3D Printing Poster

Indu Kant Deo · Youngsoo Choi · Saad Khairallah · Alexandre Reikher · Maria Strantza

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Port-Hamiltonian Neural Networks for Learning Coupled Systems and Their Interactions Poster

Razmik A. Khosrovian · Takaharu Yaguchi · Takashi Matsubara

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Neural Embeddings Evolve as Interacting Particles Poster

Rohan Mehta · Ziming Liu · Max Tegmark

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Learning Fluid-Directed Rigid Body Control Poster

Kārlis Freivalds · Oskars Teikmanis · Laura Leja · Saltanovs Rodions · Ralfs Āboliņš

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Path-minimizing Latent ODEs as Inference Models Poster

Matt Sampson · Peter Melchior

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Dyson Brownian motion and random matrix dynamics of weight matrices during learning Poster

Gert Aarts · Ouraman Hajizadeh · Biagio Lucini · Chanju Park

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Bayesian Deconvolution of Astronomical Images with Diffusion Models: Quantifying Prior-Driven Features in Reconstructions Poster

Alessio Spagnoletti · Marc Huertas-Company · Alexandre Boucaud · Wassim Kabalan · Biswajit Biswas

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TELD: Trajectory-Level Langevin Dynamics for Versatile Constrained Sampling Poster

Magnus Petersen · Gemma Roig · Roberto Covino

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Point cloud diffusion models for the Electron-Ion Collider Poster

Fernando Torales Acosta · Vinicius Mikuni · Felix Ringer · Nobuo Sato · Richard Whitehill

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Generation and Human-Expert Evaluation of Interesting Research Ideas using Knowledge Graphs and Large Language Models Poster

Xuemei Gu · Mario Krenn

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Geometry-aware PINNs for Turbulent Flow Prediction Poster

Shinjan Ghosh · Julian Busch · Georgia Olympia Brikis · Biswadip Dey

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Real-time Position Reconstruction for the KamLAND-Zen Experiment using Hardware-AI Co-design Poster

Alexander Migala · Eugene Ku · Zepeng Li · Aobo Li

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fBm-Based Generative Inpainting for the Reconstruction of Chromosomal Distances Poster

Alexander Lobashev · Dmitry Guskov · Kirill Polovnikov

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Neural Infalling Clouds: Increasing the Efficacy of Subgrid Models and Scientific Equation Discovery using Neural ODEs and Symbolic Regression Poster

Brent Tan

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Automated discovery of large-scale, noise-robust experimental designs in super-resolution microscopy Poster

Carla Rodríguez · Sören Arlt · Leonhard Möckl · Mario Krenn

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Climate PAL: Climate Analysis through Conversational AI Poster

Sonia Cromp · Behrad Rabiei · Maxwell Elling · Alexander J. Herron · Michael Hendrickson

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MRI Parameters Mapping via Variational Inference Poster

Moucheng Xu · Yukun Zhou · Tobias Goodwin-Allcock · Kimia Firoozabadi · Joseph Jacob · Daniel Alexander · Paddy Slator

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Learning Pore-scale Multi-phase Flow from Experimental Data with Graph Neural Network Poster

Yuxuan Gu · Catherine Spurin · Gege Wen

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FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition Poster

Milad Ramezankhani · Rishi Parekh · Anirudh Deodhar · Dagnachew Birru

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CODES: Benchmarking Coupled ODE Surrogates Poster

Robin Janssen · Immanuel Sulzer · Tobias Buck

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First High-Resolution Galaxy Simulations Accelerated by a 3D Surrogate Model for Supernovae Poster

Keiya Hirashima · Kana Moriwaki · Michiko Fujii · Yutaka Hirai · Takayuki Saitoh · Junichiro Makino · Ulrich Steinwandel · Shirley Ho

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Multidimensional Deconvolution with Profiling Poster

Huanbiao Zhu · Mikael Kuusela · Larry Wasserman · Benjamin Nachman · Krish Desai · Vinicius Mikuni

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ChemLit-QA: A human evaluated dataset for chemistry RAG tasks Poster

Geemi Wellawatte · Philippe Schwaller · Huixuan Guo · Marta Brucka · Anna Borisova · Matthew Hart · Magdalena Lederbauer

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Embedding Theoretical Baselines For Satellite Force Estimations Poster

Benjamin Y. J. Wong · Sai Ramesh · Boo Cheong Khoo

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Evaluating Sparse Galaxy Simulations via Out-of-Distribution Detection and Amortized Bayesian Model Comparison Poster

Lingyi Zhou · Stefan Radev · William H. Oliver · Aura Obreja · Zehao Jin · Tobias Buck

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RoBo6: Standardized MMT Light Curve Dataset for Rocket Body Classification Poster

Daniel Kyselica · Marek Suppa · Jiří Šilha · Roman Ďurikovič

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CURIE: Evaluating LLMs on Multitask Scientific Long-Context Understanding and Reasoning Poster

Hao Cui · Zahra Shamsi · Xuejian Ma · Gowoon Cheon · Shutong Li · Maria Tikhanovskaya · Nayantara Mudur · Martyna Plomecka · Peter Norgaard · Paul Raccuglia · Victor V. Albert · Yasaman Bahri · Pranesh Srinivasan · Haining Pan · Philippe Faist · Brian Rohr · Michael Statt · Dan Morris · Drew Purves · Elise Kleeman · Ruth Alcantara · Matthew Abraham · Muqthar Mohammad · Ean Phing VanLee · Chenfei Jiang · Elizabeth Dorfman · Eun-Ah Kim · Michael Brenner · Sameera Ponda · Subhashini Venugopalan

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Neural 3D Reconstruction of 21-cm Tomographic Data Poster

Nashwan Sabti · Ram Purandhar Reddy Sudha · Julian Muñoz · Siddharth Mishra-Sharma · Taewook Youn

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Bumblebee: Foundational Model for Particle Physics Discovery Poster

Andrew Wildridge · Jack Rodgers · Mia Liu · Yao Yao · Andreas Jung · Ethan Colbert

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From particle clouds to tokens: building foundation models for particle physics Poster

Joschka Birk · Anna Hallin · Gregor Kasieczka

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A method for identifying causality in the response of nonlinear dynamical systems Poster

Joseph Massingham · Ole Nielsen · Tore Butlin

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LLM Enhanced Bayesian Optimization for Scientific Applications like Fusion Poster

Sahand Ghorbanpour · Ricardo Luna Gutierrez · Vineet Gundecha · Desik Rengarajan · Ashwin Ramesh Babu · Soumyendu Sarkar

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PolarBERT: A Foundation Model for IceCube Poster

Inar Timiryasov · Jean-Loup Tastet · Oleg Ruchayskiy

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Product Manifold Machine Learning for Physics Poster

Nate Woodward · Sangeon Park · Gaia Grosso · Jeffrey Krupa · Philip Harris

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Differentiable Conservative Radially Symmetric Fluid Simulations and Stellar Winds $\circ$ jf1uids Poster

Leonard Storcks · Tobias Buck

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DYffCast: Regional Precipitation Nowcasting Using IMERG Satellite Data. A case study over South America Poster

Daniel Seal · Rossella Arcucci · Salva Rühling Cachay · César Quilodrán-Casas

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Synax: A Differentiable and GPU-accelerated Synchrotron Simulation Package Poster

Kangning Diao · Zequn Li · Richard Grumitt · Yi Mao

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Transfer Learning in Materials Informatics: structure-property relationships through minimal but highly informative multimodal input Poster

Dario Massa · Grzegorz Kaszuba · Stefanos Papanikolaou · Piotr Sankowski

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Variational Loss Landscapes for Periodic Orbits Poster

Leo Yao · Ziming Liu · Max Tegmark

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Learning Locally Adaptive Metrics that Enhance Structural Representation with LAMINAR Poster

Christian Kleiber · William H. Oliver · Tobias Buck

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Explicit and data-Efficient Encoding via Gradient Flow Poster

Kyriakos Flouris · Anna Volokitin · Gustav Bredell · Ender Konukoglu

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Which bits went where? Past and future transfer entropy decomposition with the information bottleneck Poster

Kieran Murphy · Zhuowen Yin · Danielle S Bassett

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Fast GPU-Powered and Auto-Differentiable Forward Modeling of IFU Data Cubes Poster

Ufuk Çakır · Anna Schaible · Tobias Buck

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Cosmological super-resolution of the 21-cm signal Poster

Simon Pochinda · Jiten Dhandha · Anastasia Fialkov · Eloy de Lera Acedo

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Diffusion-Based Inpainting of Corrupted Spectrogram Poster

Mahsa Massoud · Reyhane Askari Hemmat · Kai-Feng Chen · Jiakun Liu · Siamak Ravanbakhsh

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Uncertainty-Penalized Bayesian Information Criterion for Parametric Partial Differential Equation Discovery Poster

Pongpisit Thanasutives · Ken-ichi Fukui

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Testing Uncertainty of Large Language Models for Physics Knowledge and Reasoning Poster

Elizaveta Reganova · Peter Steinbach

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Normalising Flow for Joint Cosmological Analysis Poster

Arrykrishna Mootoovaloo · David Alonso · Jaime Ruiz-Zapatero · Carlos Garcia-Garcia

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Dynamic Curriculum Regularization for Enhanced Training of Physics-Informed Neural Networks Poster

Callum Duffy · Gergana V Velikova

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Inferring Stability Properties of Chaotic Systems on Autoencoders’ Latent Spaces Poster

Elise Özalp · Luca Magri

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A neural surrogate solver for radiation transfer Poster

Aleksei Sorokin · Xiaoyi Lu · Yi Wang

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Meta-Learned Bayesian Optimization for Energy Yield in Inertial Confinement Fusion Poster

Vineet Gundecha · Ricardo Luna Gutierrez · Sahand Ghorbanpour · Desik Rengarajan · Rahman Ejaz · Varchas Gopalaswamy · Riccardo Betti · Soumyendu Sarkar

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Towards Commercialization of Tokamaks: Time Series Viewmakers for Robust Disruption Prediction Poster

Dhruva Chayapathy · Tavis Siebert · Akshata Kishore Moharir · Lucas Spangher · Om Patil · Cristina Rea

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Zephyr quantum-assisted hierarchical Calo4pQVAE for particle-calorimeter interactions Poster

Ian Lu · Hao Jia · Sebastian Gonzalez · Deniz Sogutlu · J. Quetzalcoatl Toledo-Marin · Sehmimul Hoque · Abhishek Abhishek · Colin Gay · Roger Melko · Eric Paquet · Geoffrey Fox · Maximilian Swiatlowski · Wojciech Fedorko

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CASBI – Chemical Abundance Simulation-Based Inference for Galactic Archeology Poster

Giuseppe Viterbo · Tobias Buck

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Symbolic regression for precision LHC physics Poster

Manuel Morales Alvarado · Josh Bendavid · Daniel Conde · Veronica Sanz · Maria Ubiali

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Explainable Deep Learning Framework for SERS Bio-quantification Poster

Jihan K. Zaki · Jakub Tomasik · Sabine Bahn · Jade McCune · Pietro Lió · Oren Scherman

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Topological data analysis of large swarming dynamics Poster

Yoh-ichi Mototake · Shinichi Ishida · Norihiro Maruyama · Takashi Ikegami

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Higher-order cumulants in diffusion models Poster

Gert Aarts · Ntiaa Entin Habibi · Lingxiao Wang · Kai Zhou

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Galaxy Formation and Evolution via Phase-temporal Clustering with FuzzyCat $\circ$ AstroLink Poster

William H. Oliver · Tobias Buck

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DeepUQ: A Systematic Comparison of Aleatoric Uncertainties from Deep Learning Methods Poster

Becky Nevin · Brian Nord · Aleksandra Ciprijanovic

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Fine-tuning Foundation Models for Molecular Dynamics: A Data-Efficient Approach with Random Features Poster

Pietro Novelli · Luigi Bonati · Pedro J. Buigues · Giacomo Meanti · Lorenzo Rosasco · Michele Parrinello · Massimiliano Pontil

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Deep Multimodal Representation Learning for Stellar Spectra Poster

Tobias Buck · Christian Schwarz

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WOTAN: Weakly-supervised Optimal Transport Attention-based Noise Mitigation Poster

Nathan Suri · Vinicius Mikuni · Benjamin Nachman

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Multi-Wavelength Analysis of Kilonova Associated with GRB 230307A: Accelerated Parameter Estimation and Model Selection Through Likelihood-Free Inference Poster

P. Darc · Clecio Roque Bom · Gabriel Teixeira · Charles Kilpatrick · Nora Sherman · Marcelo Portes de Albuquerque · Paulo Russano

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A Physics-Informed Autoencoder-NeuralODE Framework (Phy-ChemNODE) for Learning Complex Fuel Combustion Kinetics Poster

Tadbhagya Kumar · Pinaki Pal · Anuj Kumar

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Integrating Generative and Physics-Based Models for Ptychographic Imaging with Uncertainty Quantification Poster

Canberk Ekmekci · Tekin Bicer · Zichao Di · Junjing Deng · Mujdat Cetin

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History-Matching of Imbibition Flow in Multiscale Fractured Porous Media Using Physics-Informed Neural Networks (PINNs) Poster

Jassem Abbasi · Ben Moseley · Takeshi Kurotori · Ameya Jagtap · Anthony Kovscek · Aksel Hiorth · Pål Andersen

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Reconstructing micro-magnetic vector fields based on topological charge distributions via generative neural network systems Poster

Kyra Klos · Jan Disselhoff · Karin Everschor-Sitte · Friederike Schmid

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Physics-informed Discovery of State Variables in Second-Order and Hamiltonian Systems Poster

Félix Chavelli · Zi-Yu Khoo · Dawen Wu · Jonathan Low · Stéphane Bressan

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Systematic Uncertainties and Data Complexity in Normalizing Flows Poster

Sandip Roy · Yonatan Kahn · Jessie Shelton · Victoria Tiki

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Fast probabilistic galaxy field generation with diffusion models Poster

Tanner Sether · Elena Giusarma · Mauricio Reyes Hurtado

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Using transfer learning to improve the generalization of machine learning models for photometric redshift estimation Poster

Jonathan Soriano · Srinath Saikrishnan · Vikram Seenivasan · Bernie Boscoe · Jack Singal · Tuan Do

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Multimodal multi-output ordinal regression for discovering gravitationally-lensed transients Poster

Nicolò Oreste Pinciroli Vago · Piero Fraternali

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Gaussian Processes for Probabilistic Estimates of Earthquake Ground Shaking: A 1-D Proof-of-Concept Poster

Sam A. Scivier · Tarje Nissen-Meyer · Paula Koelemeijer · Atilim Gunes Baydin

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Physics-based Differentiable X-ray Rendering Improves Unsupervised 3D CBCT Reconstruction Poster

Mohammadhossein Momeni · Vivek Gopalakrishnan · Neel Dey · Polina Golland · Sarah Frisken

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Towards Using Large Language Models and Deep Reinforcement Learning for Inertial Fusion Energy Poster

Vadim Elisseev · Massimiliano Esposito · James Sexton

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An end-to-end generative model for heavy-ion collisions Poster

Jing-An Sun

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Shaping Flames with Differentiable Physics Simulations Poster

Laura Leja · Kārlis Freivalds · Oskars Teikmanis

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Jrystal: A JAX-based Differentiable Density Functional Theory Framework for Materials Poster

Tianbo Li · Zekun Shi · Stephen Dale · Giovanni Vignale · Min Lin

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Towards long rollout of neural operators with local attention and flow matching-inspired correction: An example in frontal polymerization PDEs Poster

Pengfei Cai · Sulin Liu · Qibang Liu · Philippe Geubelle · Rafael Gomez-Bombarelli

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LensPINN: Physics Informed Neural Network for Learning Dark Matter Morphology in Lensing Poster

Ashutosh Ojha · Sergei Gleyzer · Michael Toomey · Pranath Reddy Kumbam

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Diffusion-Based Inverse Solver on Function Spaces With Applications to PDEs Poster

Abbas Mammadov · Julius Berner · Kamyar Azizzadenesheli · Jong Chul Ye · Animashree Anandkumar

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Dissipativity-Informed Learning for Chaotic Dynamical Systems with Attractor Characterization Poster

Sunbochen Tang · Themis Sapsis · Navid Azizan

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Taylor Mode Neural Operators: Enhancing Computational Efficiency in Physics-Informed Neural Operators Poster

Anas Jnini · Flavio Vella

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GeoWavelets: Spherical Wavelets for Fair Implicit Representations of Earth Data Poster

Daniel Cai · Randall Balestriero

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Uncertainty Quantification From Scaling Laws in Deep Neural Networks Poster

Ibrahim Elsharkawy · Yonatan Kahn · Benjamin Hooberman

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SE(3) Equivariant Topologies for Structure-based Drug Discovery Poster

Alvaro Prat · Roy Tal Dew · Hisham Aty · Aurimas Pabrinkis · Orestis Bastas · Tanya Paquet · Gintautas Kamuntavicius · Roy Tal

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Learning dictionaries of New Physics with sparse local kernels Poster

Gaia Grosso · Philip Harris · Ekaterina Govorkova · Eric Moreno · Ryan Raikman

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Unlocking Ion-Scale Coherent Structures in the Solar Wind with Machine Learning Poster

Yufei Yang

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Live Constrained Deep Learning Models Optimize Unmanned Underwater Vehicle Control Systems Poster

Brian Zhou · Kamal Viswanath · Jason Geder

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Mean-Field Simulation-Based Inference for Cosmological Initial Conditions Poster

Oleg Savchenko · Florian List · Noemi Anau Montel · Christoph Weniger · Guillermo Franco Abellán

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AICircuit: A Multi-Level Dataset and Benchmark for AI-Driven Analog Integrated Circuit Design Poster

Asal Mehradfar · Xuzhe Zhao · Yue Niu · Sara Babakniya · Mahdi Alesheikh · Hamidreza Aghasi · Salman Avestimehr

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Constrained Synthesis with Projected Diffusion Models Poster

Jacob K Christopher · Stephen Baek · Nando Fioretto

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MATEY: multiscale adaptive foundation models for spatiotemporal physical systems Poster

Pei Zhang · M. Laiu · Matthew Norman · Doug Stefanski · John Gounley

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Neural rendering enables dynamic tomography Poster

Ivan Grega · Will Whitney · Vikram Deshpande

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A machine learning approach to duality in statistical physics Poster

Prateek Gupta · Andrea Ferrari · Nabil Iqbal

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Interpreting Multi-band Galaxy Observations with Large Language Model-Based Agents Poster

Zechang Sun · Yuan-Sen Ting · Yaobo Liang · Nan Duan · Song Huang · Zheng Cai

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No Location Left Behind: Introducing the Fairness Assessment for Implicit Representations of Earth Data Poster

Daniel Cai · Randall Balestriero

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PICL: Learning to Incorporate Physical Information When Only Coarse-Grained Data is Available Poster

Haodong Feng · Yue Wang · Dixia Fan

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Quantum Wasserstein Compilation: Unitary Compilation using the Quantum Earth Mover's Distance Poster

Marvin Richter · Abhishek Dubey · Axel Plinge · Christopher Mutschler · Daniel Scherer · Michael Hartmann

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Randomized reward redistribution for HPGe waveform classification under weakly-supervised learning setup Poster

Sonata Simonaitis-Boyd · Aobo Li

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Unpaired Translation of Point Clouds for Modeling Detector Response Poster

Mingyang Li · Curtis Hunt · Michelle Kuchera · Raghuram Ramanujan · Yassid Ayyad · Adam Anthony

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Can KANs (re)discover predictive models for Direct-Drive Laser Fusion? Poster

Rahman Ejaz · Varchas Gopalaswamy · Aarne Lees · Riccardo Betti · Christopher Kanan

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Conditional Diffusion Models for Generating Images of SDSS-Like Galaxies Poster

Mikaeel Yunus · John Wu · Timothy Heckman · Benne Holwerda

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Video-Driven Graph Network-Based Simulators Poster

Franciszek Szewczyk · Gilles Louppe · Matthia Sabatelli

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Uncertainty Quantification for Surface Ozone Emulators using Deep Learning Poster

Kelsey Doerksen · Yuliya Marchetti · James Montgomery · Yarin Gal · Freddie Kalaitzis · Kazuyuki Miyazaki · Kevin Bowman · Steven Lu

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Towards Agentic AI on Particle Accelerators Poster

Antonin Sulc · Thorsten Hellert · Raimund Kammering · Hayden Hoschouer · Jason St. John

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Hamiltonian Learning using Machine Learning Models Trained with Continuous Measurements Poster

Amit Rege · Kristopher Tucker · Conor Smith · Claire Monteleoni

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Efficient and Unbiased Sampling of Boltzmann Distributions via Consistency Models Poster

Fengzhe Zhang · Jiajun He · Laurence Midgley · Javier Antorán · José Miguel Hernández-Lobato

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Neural Network Simulation of Time-variant Waves on Arbitrary Grids with Applications in Active Sonar Poster

Yash Ranjith

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Meta-Designing Quantum Experiments with Language Models Poster

Sören Arlt · Haonan Duan · Felix Li · Sang Michael Xie · Yuhuai Wu · Mario Krenn

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Amortizing intractable inference in diffusion models for Bayesian inverse problems Poster

Siddarth Venkatraman · Moksh Jain · Luca Scimeca · Minsu Kim · Marcin Sendera · Mohsin Hasan · Luke Rowe · Sarthak Mittal · Pablo Lemos · Emmanuel Bengio · Alexandre Adam · Jarrid Rector-Brooks · Yashar Hezaveh · Laurence Perreault-Levasseur · Yoshua Bengio · Glen Berseth · Nikolay Malkin

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Evidential deep learning for probabilistic modelling of extreme storm events Poster

Ayush Khot · Xihaier Luo · Ai Kagawa · Shinjae Yoo

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Score-based models for 1/f correlated noise correction in James Webb Space Telescope spectral data Poster

Salma Salhi · Alexandre Adam · Loic Albert · Rene Doyon · Laurence Perreault-Levasseur

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Physics-guided Optimization of Photonic Structures using Denoising Diffusion Probabilistic Models Poster

Dongjin Seo · Soobin Um · Sangbin Lee · Jong Chul Ye · Haejun Chung

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Generation of Air Shower Images for Imaging Air Cherenkov Telescopes using Diffusion Models Poster

Christian Elflein · Stefan Funk · Jonas Glombitza · Vinicius Mikuni · Benjamin Nachman · Lark Wang

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Clifford Flows Poster

Francesco Alesiani · Takashi Maruyama

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Scalable nonlinear manifold reduced order model for dynamical systems Poster

Ivan Zanardi · Alejandro N. Diaz · Seung Whan Chung · Marco Panesi · Youngsoo Choi

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ClariPhy: Physics-Informed Image Deblurring with Transformers for Hydrodynamic Instability Analysis Poster

Shai Stamler-Grossman · Nadav Schneider · Gershon Hanoch · Gal Oren

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Convolutional Vision Transformer for Cosmology Parameter Inference Poster

Yash Gondhalekar · Kana Moriwaki

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PINNfluence: Influence Functions for Physics-Informed Neural Networks Poster

Jonas Naujoks · Aleksander Krasowski · Moritz Weckbecker · Thomas Wiegand · Sebastian Lapuschkin · Wojciech Samek · René P. Klausen

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Speak so a physicist can understand you! TetrisCNN for detecting phase transitions and order parameters Poster

Kacper Cybiński · James Enouen · Antoine Georges · Anna Dawid

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Interpreting Transformers for Jet Tagging Poster

Aaron Wang · Abhijith Gandrakota · Elham E Khoda · Vivekanand Gyanchand Sahu · Javier Duarte · Priyansh Bhatnagar · Jennifer Ngadiuba

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Deep Learning Based Superconductivity Prediction and Experimental Tests Poster

Daniel Kaplan · Adam Zheng · Joanna Blawat · Rongying Jin · Viktor Oudovenko · Gabriel Kotliar · Weiwei Xie · Anirvan Sengupta

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Emulation and Assessment of Gradient-Based Samplers in Cosmology Poster

Arrykrishna Mootoovaloo · David Alonso · Jaime Ruiz-Zapatero · Carlos Garcia-Garcia

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Unsupervised Physics-Informed Super-Resolution of Strong Lensing Images for Sparse Datasets Poster

Anirudh Shankar · Michael Toomey · Sergei Gleyzer

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A Poisson-process AutoDecoder for Astrophysical, Time-variable, X-ray Sources Poster

Yanke Song · V Villar · Rafael Martínez-Galarza

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Graph rewiring for long range-aware protein learning Poster

Ali Hariri · Pierre Vandergheynst

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Evolutionary and Transformer based methods for Symbolic Regression Poster

Samyak Jha · Sergei Gleyzer · Eric Reinhardt · Victor Baules · Francois Charton · Nobuchika Okada

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Open-Source Molecular Processing Pipeline for Generating Molecules Poster

Shreyas V · Jose Siguenza · Karan Bania · Bharath Ramsundar

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Hybrid Prior Wavelet Flow For Extragalactic Foreground Simulations Poster

Matiwos Mebratu · W.L. Wu

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Toward Model-Agnostic Detection of New Physics Using Data-Driven Signal Regions Poster

Soheun Yi · John Alison · Mikael Kuusela

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