Workshop

NeurIPS 2023 Workshop: Machine Learning and the Physical Sciences

Brian Nord · Atilim Gunes Baydin · Adji Bousso Dieng · Emine Kucukbenli · Siddharth Mishra-Sharma · Benjamin Nachman · Kyle Cranmer · Gilles Louppe · Savannah Thais

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Abstract

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

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Schedule

Timezone: America/Los_Angeles

6:15 AM

Opening remarks Introductory remarks by the organizers

Video

6:30 AM

Benefits of Approximate and Partial Equivariance Invited talk

Shubhendu Trivedi

Video

6:55 AM

Interpretable deep learning for protein modeling Invited talk

Maria Rodriguez Martinez · Maria Rodriguez Martinez

Video

7:20 AM

Panel on inductive biases and interpretability Panel discussion

Shubhendu Trivedi · Anuj Karpatne · Joshua Speagle · Savannah Thais

Video

8:15 AM

Coffee break Coffee break

8:45 AM

Removing Dust from CMB Observations with Diffusion Models Contributed talk

David Heurtel-Depeiges

Video

9:00 AM

Poster session 1 Poster session

Link

10:00 AM

Lunch break Lunch break

11:30 AM

What's missing? A speculative sketch of the future of machine learning and science Invited talk

Alexander Alemi

Video

12:00 PM

Poster session 2 Poster session

Link

1:15 PM

Coffee break Coffee break

1:30 PM

Towards an Astronomical Foundation Model for Stars Contributed talk

Henry Leung

Video

1:45 PM

KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images Contributed talk

Rembert Daems

Video

Link

2:00 PM

Ultra Fast Transformers on FPGAs for Particle Physics Experiments Contributed talk

Elham E Khoda

Video

2:15 PM

Panel on institutional support and funding Panel discussion

Jesse Thaler · Max Welling · John Wu · Sara Hooker

Video

3:15 PM

Closing remarks Closing remarks by the organizers

Video

Control-aware echo state networks (Ca-ESN) for the suppression of extreme events Poster

Alberto Racca · Luca Magri

KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images Poster

Rembert Daems · · Francis Wyffels · Guillaume Crevecoeur

Incorporating Additive Separability into Hamiltonian Neural Networks for Regression and Interpretation Poster

Zi-Yu Khoo · Jonathan Sze Choong Low · Stéphane Bressan

Extracting an Informative Latent Representation of High-Dimensional Galaxy Spectra Poster

Daiki Iwasaki · Suchetha Cooray · Tsutomu Takeuchi

When Black-box PDE Solvers Meet Deep Learning: End-to-End Mesh Optimization for Efficient Fluid Flow Prediction Poster

Shaocong Ma · James Diffenderfer · Bhavya Kailkhura · Yi Zhou

Physics-consistency of infinite neural networks Poster

Sascha Ranftl

Pay Attention to Mean Fields for Point Cloud Generation Poster

Benno Käch · Isabell Melzer · Dirk Krücker

Simulation-based Inference for Cardiovascular Models Poster

Antoine Wehenkel · Jens Behrmann · Andy Miller · Guillermo Sapiro · Ozan Sener · Marco Cuturi · Joern-Henrik Jacobsen

Fast SoC thermal simulation with physics-aware U-Net Poster

Yu-Sheng Lin · Li-Song Lin · Chin-Jui Chang · Ting-Yu Lin · Shih-Hong Pan · Ya-Wen Yu · Kai-En Yang · Wei Cheng Lee · Yi-Chen Lin · Tai-Yu Chen · Jason Yeh

Unsupervised segmentation of irradiation-induced order–disorder phase transitions in electron microscopy Poster

Arman Ter-Petrosyan · Jenna A Bilbrey · Christina Doty · Bethany Matthews · Le Wang · Yingge Du · Eric Lang · Khalid Hattar · Steven Spurgeon

Attention-guided neural differential equations for physics-constrained deep learning of ion transport Poster

Danyal Rehman · John Lienhard

Learning Closure Relations using Differentiable Programming: An Example in Radiation Transport Poster

Aidan Crilly · Benjamin Duhig · Nacime Bouziani

Link

DFT Hamiltonian Neural Network Training with Semi-supervised Learning Poster

Yucheol Cho · Guenseok Choi · Gyeongdo Ham · Mincheol Shin · Dae-Shik Kim

CaloLatent: Score-based Generative Modelling in the Latent Space for Calorimeter Shower Generation Poster

Thandikire Madula · Vinicius Mikuni

Predicting Galaxy Interloper Fraction with GNNs Poster

Elena Massara · Francisco Villaescusa · Will Percival

ML-Enhanced Generalized Langevin Equation for Transient Anomalous Diffusion in Polymer Dynamics Poster

Gian-Michele Cherchi · Alain Dequidt · Patrice Hauret · Arnaud Guillin · Vincent Barra · Nicolas Martzel

Link

Ensemble models outperform single model uncertainties and predictions for operator-learning of hypersonic flows Poster

Victor Leon · Noah Ford · Honest Mrema · Jeffrey Gilbert · Alexander New

A Multi-Grained Group Symmetric Framework for Learning Protein-Ligand Binding Dynamics Poster

Shengchao Liu · weitao du · Yanjing Li · Nakul Rampal · Zhuoxinran Li · Vignesh Bhethanabotla · Omar Yaghi · Christian Borgs · Anima Anandkumar · Hongyu Guo · Jennifer Chayes

Discovering Black Hole Mass Scaling Relations with Symbolic Regression Poster

Zehao Jin · Benjamin Davis

Hydrogen Diffusion through Polymer using Deep Reinforcement Learning Poster

Tian Sang · Ken-ichi Nomura · Aiichiro Nakano · Rajiv Kalia · Priya Vashishta

Nonlinear-manifold reduced order models with domain decomposition Poster

Alejandro Diaz · Youngsoo Choi · Matthias Heinkenschloss

A Multimodal Dataset and Benchmark for Radio Galaxy and Infrared Host Detection Poster

Nikhel Gupta

PINNs-TF2: Fast and User-Friendly Physics-Informed Neural Networks in TensorFlow V2 Poster

Reza Akbarian Bafghi · Maziar Raissi

Link

Extending Explainable Boosting Machines to Scientific Image Data Poster

Daniel Schug · Sai Yerramreddy · Rich Caruana · Craig Greenberg · Justyna Zwolak

Fast Detection of Phase Transitions with Multi-Task Learning-by-Confusion Poster

Julian Arnold · Frank Schäfer · Niels Lörch

A Data-Driven, Non-Linear, Parameterized Reduced Order Model of Metal 3D Printing Poster

Aaron Brown · Eric Chin · Youngsoo Choi · Saad Khairallah · Joseph McKeown

Evaluating Physically Motivated Loss Functions for Photometric Redshift Estimation Poster

Andrew Engel · Jan Strube

Variational quantum dynamics of two-dimensional rotor models Poster

Matija Medvidović · Dries Sels

Pre-training strategy using real particle collision data for event classification in collider physics Poster

Tomoe Kishimoto · Masahiro Morinaga · Masahiko Saito · Junichi Tanaka

Zephyr : Stitching Heterogeneous Training Data with Normalizing Flow for Photometric Redshift Inference Poster

Zechang Sun · Joshua Speagle · Song Huang · Yuan-Sen Ting · Zheng Cai

Data-Driven Autoencoder Numerical Solver with Uncertainty Quantification for Fast Physical Simulations Poster

Christophe Bonneville · Youngsoo Choi · Debojyoti Ghosh · Jon Belof

Uncovering Conformal Towers Using Deep Learning Poster

Lior Oppenheim · Zohar Ringel · Snir Gazit · Maciej Koch-Janusz

Incremental learning for physics-informed neural networks Poster

Aleksandr Dekhovich · Marcel Sluiter · David M.J. Tax · Miguel Bessa

GAMMA: Galactic Attributes of Mass, Metallicity, and Age Dataset Poster

Tobias Buck · Ufuk Çakır

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Differential optimisation for task- and constraint-aware design of particle detectors Poster

Giles Strong · Maxime Lagrange · Aitor Orio Alonso · Anna Bordignon · Florian Bury · tommaso dorigo · Andrea Giammanco · Mariam Safieldin · Jan Kieseler · Max Lamparth · Pablo Martinez · Federico Nardi · Pietro Vischia · Haitham Zaraket

Neural ODEs as a discovery tool to characterize the structure of the hot galactic wind of M82 Poster

Dustin Nguyen · Yuan-Sen Ting · Todd Thompson · Sebastian Lopez · Laura Lopez

Speeding up astrochemical reaction networks with autoencoders and neural ODEs Poster

Tobias Buck · Immanuel Felix Sulzer

GalacticFlow: Learning a Generalized Representation of Galaxies with Normalizing Flows Poster

Tobias Buck · Luca Wolf

PACuna: Automated Fine-Tuning of Language Models for Particle Accelerators Poster

Antonin Sulc · Raimund Kammering · Annika Eichler · Tim Wilksen

Graph-Theoretical Approaches for AI-Driven Discovery in Quantum Optics Poster

Xuemei Gu · Carlos Ruiz-Gonzalez · Sören Arlt · Tareq Jaouni · Jan Petermann · Sharareh Sayyad · Ebrahim Karimi · Nora Tischler · Mario Krenn

Direct Amortized Likelihood Ratio Estimation Poster

Adam Cobb · Brian Matejek · Daniel Elenius · Anirban Roy · Susmit Jha

Physics-informed neural networks with unknown measurement noise Poster

Philipp Pilar · Niklas Wahlström

Universal Semantic-less Texture Boundary Detection for Microscopy (and Metallography) Poster

Matan Rusanovsky · Ofer Beeri · Shai Avidan · Gal Oren

Information bottleneck learns dominant transfer operator eigenfunctions in dynamical systems Poster

Matthew S. Schmitt · Maciej Koch-Janusz · Michel Fruchart · Daniel Seara · Vincenzo Vitelli

Causa prima: cosmology meets causal discovery for the first time Poster

Mario Pasquato · Zehao Jin · Pablo Lemos · Benjamin Davis · Andrea Macciò

Unraveling the Mysteries of Galaxy Clusters: Recurrent Inference Deconvolution of X-ray Spectra Poster

Carter Rhea · Julie Hlavacek-Larrondo · Ralph Kraft · Akos Bogdan · Laurence Perreault-Levasseur · Alexandre Adam · John Zuhone

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

Kevin Chung · Youngsoo Choi · Pratanu Roy · Thomas Moore · Thomas Roy · Tiras Y. Lin · Sarah Baker

Improving dispersive readout of a superconducting qubit by machine learning on path signature Poster

Shuxiang Cao · Zhen Shao · Jian-Qing Zheng · Mustafa Bakr · Peter Leek · Terry Lyons

Optimizing Likelihood-free Inference using Self-supervised Neural Symmetry Embeddings Poster

Deep Chatterjee · Philip Harris · Maanas Goel · Malina Desai · Michael Coughlin · Erik Katsavounidis

Removing Dust from CMB Observations with Diffusion Models Poster

David Heurtel-Depeiges · Blakesly Burkhart · Ruben Ohana · Bruno Régaldo-Saint Blancard

$\rho$-Diffusion: A diffusion-based density estimation framework for computational physics Poster

Maxwell Xu Cai · Kin Long Kelvin Lee

Transformers for Scattering Amplitudes Poster

Garrett Merz · Francois Charton · Tianji Cai · Kyle Cranmer · Lance Dixon · Niklas Nolte · Matthias Wilhelm

NeuralHMC: Accelerated Hamiltonian Monte Carlo with a Neural Network Surrogate Likelihood Poster

Linnea Wolniewicz · Peter Sadowski · Claudio Corti

Discovering Galaxy Features via Dataset Distillation Poster

Haowen Guan · Xuan Zhao · Zishi Wang · Zhiyang Li · Julia Kempe

Modeling Coupled 1D PDEs of Cardiovascular Flow with Spatial Neural ODEs Poster

Hunor Csala · Arvind Mohan · Daniel Livescu · Amirhossein Arzani

Generating Multiphase Fluid Configurations in Fractures using Diffusion Models Poster

Jaehong Chung · Agnese Marcato · Eric Guiltinan · Tapan Mukerji · Yen Ting Lin · Javier E. Santos

Redefining Super-Resolution:Fine-mesh PDE predictions without classical simulations Poster

Rajat Sarkar · Ritam Majumdar · Vishal Jadhav · Sagar Srinivas Sakhinana · Venkataramana Runkana

Discovering Quantum Error Correcting Codes with Deep Reinforcement Learning Poster

Jan Olle · Remmy Zen · Matteo Puviani · Florian Marquardt

Discovering Quantum Circuits for Logical State Preparation with Deep Reinforcement Learning Poster

Remmy Zen · Jan Olle · Matteo Puviani · Florian Marquardt

Differentiable Simulation of a Liquid Argon TPC for High-Dimensional Calibration Poster

Pierre Granger

Learning Hard Distributions with Quantum-enhanced Variational Autoencoders Poster

Anantha Rao · Dhiraj Madan · Anupama Ray · Dhinakaran Vinayagamurthy · M S Santhanam

Revealing the Mechanism of Large-scale Gradient Systems Using a Neural Reduced Potential Poster

Shunya Tsuji · Ryo Murakami · Hayaru Shouno · Yoh-ichi Mototake

Physical Symbolic Optimization Poster

Wassim Tenachi · Rodrigo Ibata · Foivos Diakogiannis

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Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model Poster

François Rozet · Gilles Louppe

Physics-Informed Tensor Basis Neural Network for Turbulence Closure Modeling Poster

Leon Riccius · Atul Agrawal · Phaedon S Koutsourelakis

Relating Generalization in Deep Neural Networks to Sensitivity of Discrete Dynamical Systems Poster

Jan Disselhoff · Michael Wand

Orbital-Free Density Functional Theory with Continuous Normalizing Flows Poster

Rodrigo Vargas-Hernandez · Ricky T. Q. Chen · Alexandre de Camargo

DeepTreeGANv2: Iterative Pooling of Point Clouds Poster

Moritz A.W. Scham · Dirk Krücker · Kerstin Borras

Robust Ocean Subgrid-Scale Parameterizations Using Fourier Neural Operators Poster

Victor Mangeleer · Gilles Louppe

3D Localization of Microparticles from Holographic Images using Neural Networks Poster

Ayush Paliwal · Oliver Schlenczek · Birte Thiede · Gholamhossein Bagheri · Alexander Ecker

Locating Hidden Exoplanets Using Machine Learning Poster

Jason Terry · Sergei Gleyzer

Learning Optical Map in Liquid Xenon Detector with Poisson Likelihood Loss Poster

Shixiao Liang · Christopher Tunnell

AstroYOLO: Learning Astronomy Multi-Tasks in a Single Unified Real-Time Framework Poster

Nodirkhuja Khujaev · Roman Tsoy · Seungryul Baek

Coarse graining systems on inhomogeneous graphs using contrastive learning Poster

Doruk Efe Gökmen · Maciej Koch-Janusz · Zohar Ringel · Sebastian Huber · Felix Flicker · Sounak Biswas

Understanding Pathologies of Deep Heteroskedastic Regression Poster

Eliot Wong-Toi · Alex Boyd · Vincent Fortuin · Stephan Mandt

Advancing Generative Modelling of Calorimeter Showers on Three Frontiers Poster

Erik Buhmann · Sascha Diefenbacher · Engin Eren · Frank Gaede · Gregor Kasieczka · William Korcari · Anatolii Korol · Claudius Krause · Katja Krueger · Peter McKeown · Imahn Shekhzadeh · David Shih

Multi-fidelity Constrained Optimization for Stochastic Black Box Simulators Poster

Kislaya Ravi · Atul Agrawal · Phaedon S Koutsourelakis · Hans-Joachim Bungartz

Activation Functions in Non-Negative Neural Networks Poster

Marlon Becker · Dominik Drees · Frank Brückerhoff-Plückelmann · Carsten Schuck · Wolfram Pernice · Benjamin Risse

Tree-Based Algorithms for Weakly Supervised Anomaly Detection Poster

Thorben Finke · Marie Hein · Gregor Kasieczka · Michael Krämer · Alexander Mück · Parada Prangchaikul · Tobias Quadfasel · David Shih · Manuel Sommerhalder

HIDM: Emulating Large Scale HI Maps using Score-based Diffusion Models Poster

Sultan Hassan · Sambatra Andrianomena

Probabilistic-Machine-Learning-based Turbulence Model Learning with a Differentiable Solver Poster

Atul Agrawal · Phaedon S Koutsourelakis

AI ensemble for signal detection of higher order gravitational wave modes of quasi-circular, spinning, non-precessing binary black hole mergers Poster

Minyang Tian · Eliu Huerta

Latent space representations of cosmological fields Poster

Sambatra Andrianomena · Sultan Hassan

Enhancing Data-Assimilation in CFD using Graph Neural Networks Poster

Michele Quattromini · Michele Alessandro Bucci · Stefania Cherubini · Onofrio Semeraro

Gamma Ray AGNs: Estimating Redshifts and Blazar Classification using traditional Neural Networks with smart initialization and self-supervised learning Poster

Sarvesh Gharat · Gopal Bhatta · ABHIMANYU BORTHAKUR

Enhancing the local expressivity of geometric graph neural networks Poster

Sam Walton Norwood · Lars L Schaaf · Ilyes Batatia · Arghya Bhowmik · Gabor Csanyi

Domain Adaptation for Measurements of Strong Gravitational Lenses Poster

Paxson Swierc · Yifan Zhao · Aleksandra Ciprijanovic · Brian Nord

QDC: Quantum Diffusion Convolution Kernels on Graphs Poster

Thomas Markovich

Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation Poster

Ryan Liu · Abhijith Gandrakota · Jennifer Ngadiuba · jean-roch vlimant · Maria Spiropulu

Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder Poster

Ryan Liu · Abhijith Gandrakota · Jennifer Ngadiuba · jean-roch vlimant · Maria Spiropulu

Preparing Spectral Data for Machine Learning: A Study of Geological Classification from Aerial Surveys Poster

Jun Woo Chung · Alex Sim · Brian Quiter · Yuxin Wu · Weijie Zhao · Kesheng Wu

Loss-driven sampling within hard-to-learn areas for simulation-based neural network training Poster

Sofya Dymchenko · Bruno Raffin

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Long Time Series Data Release from Broadband Axion Dark Matter Experiment Poster

Jessica Fry · Aobo Li

Physics - Informed Machine Learning for Reduced Space Chemical Kinetics Poster

Anuj Kumar · Tarek Echekki

Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties Poster

Lindsey Gray · Jennet Dickinson · Rachel Kovach-Fuentes · Morris Swartz · Giuseppe Di Guglielmo · Alice Bean · Douglas Berry · Manuel Blanco Valentin · Karri DiPetrillo · Farah Fahim · Jim Hirschauer · Shruti Kulkarni · Ron Lipton · Petar Maksimovic · Corrinne Mills · Mark Neubauer · Benjamin Parpillon · Gauri Pradhan · Chinar Syal · Nhan Tran · Jieun Yoo · Aaron Young

On Representations of Mean-Field Variational Inference Poster

Soumyadip Ghosh · Yingdong Lu · Tomasz Nowicki · Edith Zhang

Active learning meets fractal decision boundaries: a cautionary tale from the Sitnikov three body problem Poster

Nicolas Payot · Mario Pasquato · Alessandro Alberto Trani · Yashar Hezaveh · Laurence Perreault-Levasseur

A deep learning framework for jointly extracting spectra and source-count distributions of count maps Poster

Florian Wolf · Florian List · Nicholas Rodd · Oliver Hahn

Machine learning-based compression of quantum many body physics: PCA and autoencoder representation of the vertex function Poster

Jiawei Zang · Matija Medvidović · Dominik Kiese · Domenico Di Sante · Anirvan Sengupta · Andy Millis

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets Poster

Andrea Roncoli · Aleksandra Ciprijanovic · M Voetberg · Francisco Villaescusa · Brian Nord

Multibasis Encodings in Recurrent Neural Network Wave Functions for Variational Optimization Poster

Wirawat Kokaew

Simulation Based Inference of BNS Kilonova Properties: A Case Study with AT2017gfo Poster

Phelipe Darc · Clecio Bom · Bernardo Fraga · Charles D. Kilpatrick

Physics-aware Modeling of an Accelerated Particle Cloud Poster

Emmanuel Goutierre · Hayg Guler · Christelle Bruni · Johanne Cohen · Michele Sebag

Optimized Dry Cooling for Solar Power Plants Poster

Hansley Narasiah · Ouail Kitouni · Andrea Scorsoglio · Bernd Sturdza · Shawn Hatcher · Dolores Garcia · Matt Kusner

A Physics-Constrained NeuralODE Approach for Robust Learning of Stiff Chemical Kinetics Poster

Tadbhagya Kumar · Anuj Kumar · Pinaki Pal

Trick or treat? Evaluating stability strategies in graph network-based simulators Poster

Omer Rochman Sharabi · Gilles Louppe

Super-Resolution Emulation of Large Cosmological Fields with a 3D Conditional Diffusion Model Poster

Adam Rouhiainen · Michael Gira · Gary Shiu · Kangwook Lee · Moritz Münchmeyer

Equivariant Networks for Robust Galaxy Morphology Classification Poster

Sneh Pandya · Purvik Patel · Franc O · Jonathan Blazek

Reduced-order modeling for parameterized PDEs via implicit neural representations Poster

Tianshu Wen · Kookjin Lee · Youngsoo Choi

Simulation-Based Inference for Detecting Blending in Spectra Poster

Declan McNamara · Jeffrey Regier

JETLOV: Enhancing Jet Tree Tagging through Neural Network Learning of Optimal LundNet Variables Poster

Giorgio Cerro

Hierarchical Cross-entropy Loss for Classification of Astrophysical Transients Poster

V Villar

Surrogate Model Training Data for FIDVR-related Voltage Control in Large-scale Power Grids Poster

Tianzhixi Yin · Renke Huang · Ramij Raja Hossain · Qiuhua Huang · Jie Tan · Wenhao Yu

Differentiable, End-to-End Forward Modeling for 21 cm Cosmology: Robust Systematics Error Budgeting and More Poster

Nicholas Kern

Investigating the Ability of PINNs To Solve Burgers’ PDE Near Finite-Time BlowUp Poster

Dibyakanti Kumar · Anirbit Mukherjee

Detection and Segmentation of Ice Blocks in Europa's Chaos Terrain Using Mask R-CNN Poster

Marina Dunn · Conor Nixon · Alyssa Mills · Ahmed Awadallah · Ethan Duncan · John Santerre · Douglas Trent · Andrew Larsen

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Neural Networks vs. Whittaker Smoothing: Advanced Techniques for Scattering Signal Removal in 3D Fluorescence spectra Poster

Aleksandr Zakuskin · Ivan Krylov · Timur Labutin

Benchmarking of Fast and Interpretable UF Machine Learning Potentials Poster

Pawan Prakash

A Physics-Informed Variational Autoencoder for Rapid Galaxy Inference and Anomaly Detection Poster

Alex Gagliano · Ashley Villar

Pythia: A prototype artificial agent for designing optimal gravitational-wave follow-up campaigns Poster

Niharika Sravan · Matthew Graham · Michael Coughlin · Shreya Anand · Tomas Ahumada

Probabilistic Reconstruction of Dark Matter fields from galaxies using diffusion models Poster

Carolina Cuesta · Yueying Ni · Core Francisco Park · Nayantara Mudur · Victoria Ono

Predicting the Age of Astronomical Transients from Real-Time Multivariate Time Series Poster

Daniel Muthukrishna

Multiscale Feature Attribution for Outliers Poster

Jeff Shen · Peter Melchior

Learning Reionization History from Quasars with Simulation-Based Inference Poster

Huanqing Chen · Joshua Speagle · Keir Rogers

Interpretable Joint Event-Particle Reconstruction at NOvA with Sparse CNNs and Transformers Poster

Alexander Shmakov · Alejandro Yankelevich · Jianming Bian · Pierre Baldi

SimSIMS: Simulation-based Supernova Ia Model Selection with thousands of latent variables Poster

Konstantin Karchev · Roberto Trotta · Christoph Weniger

Accelerating Kinetic Simulations of Electrostatic Plasmas with Reduced-Order Modeling Poster

Ping-Hsuan Tsai · Kevin Chung · Debojyoti Ghosh · John Loffeld · Youngsoo Choi · Jon Belof

Sequential Monte Carlo for Detecting and Deblending Objects in Astronomical Images Poster

Tim White · Jeffrey Regier

DeepSurveySim: Simulation Software and Benchmark Challenges for Astronomical Observation Scheduling Poster

M Voetberg · Brian Nord

LoDIP: Low-dose phase retrieval with deep image prior Poster

Raunak Manekar · Elisa Negrini · Minh Pham · Daniel Jacobs · Jaideep Srivastava · Stanley Osher · Jianwei Miao

Bayesian multi-band fitting of alerts for kilonovae detection Poster

Biswajit Biswas

Forward Gradients for Data-Driven CFD Wall Models Poster

Jan Hueckelheim · Tadbhagya Kumar · Krishnan Raghavan · Pinaki Pal

Learning an Effective Evolution Equation for Particle-Mesh Simulations Across Cosmologies Poster

Nicolas Payot · Pablo Lemos · Laurence Perreault-Levasseur · Carolina Cuesta · Chirag Modi · Yashar Hezaveh

Active Learning for Discovering Complex Phase Diagrams with Gaussian Processes Poster

Max Zhu · Jian Yao · Marcus Mynatt · Hubert Pugzlys · Shuyi Li · Qingyuan Zhao · Chunjing Jia

RACER: Rational Artificial Intelligence Car-following-model Enhanced by Reality Poster

Tianyi Li · Raphael Stern

Learned integration contour deformation for signal-to-noise improvement in Monte Carlo calculations Poster

William Detmold · Gurtej Kanwar · Yin Lin · Phiala Shanahan · Michael Wagman

The search for the lost attractor Poster

Mario Pasquato · Syphax Haddad · Pierfrancesco Di Cintio · Alexandre Adam · Noé Dia · Mircea Petrache · Ugo Niccolò Di Carlo · Alessandro Alberto Trani · Laurence Perreault-Levasseur · Yashar Hezaveh · Pablo Lemos

Field Emulation and Parameter Inference with Diffusion Models Poster

Nayantara Mudur · Carolina Cuesta · Douglas P. Finkbeiner

Symbolic Machine Learning for High Energy Physics Calculations Poster

Abdulhakim Alnuqaydan · Sergei Gleyzer · Harrison Prosper · Eric Reinhardt · Francois Charton · Neeraj Anand

Autoencoding Labeled Interpolator, Inferring Parameters From Image And Image From Parameters Poster

Ali SaraerToosi · Avery Broderick

Leveraging Deep Learning for Physical Model Bias of Global Air Quality Estimates Poster

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

Towards data-driven models of hadronization Poster

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

From Plateaus to Progress: Unveiling Training Dynamics of PINNs Poster

Daniel Lengyel · Panos Parpas · Rahil Pandya

Equivariant Neural Networks for Signatures of Dark Matter Morphology in Strong Lensing Data Poster

Geo Jolly Cheeramvelil · Michael Toomey · Sergei Gleyzer

Echoes in the Noise: Posterior Samples of Faint Galaxy Surface Brightness Profiles with Score-Based Likelihoods and Priors Poster

Alexandre Adam · Connor Stone · Connor Bottrell · Ronan Legin · Laurence Perreault-Levasseur · Yashar Hezaveh

Deep Learning Segmentation of Spiral Arms and Bars Poster

Mike Walmsley · Ashley Spindler

Accelerating Flow Simulations using Online Dynamic Mode Decomposition Poster

Seung Won Suh · Kevin Chung · Timo Bremer · Youngsoo Choi

Sparse 3D Images: Point Cloud or Image methods? Poster

Fernando Torales Acosta · Vinicius Mikuni · Benjamin Nachman · Miguel Arratia · Bishnu Karki · Ryan Milton · Piyush Karande · Aaron Angerami

Classification under Prior Probability Shift in Simulator-Based Inference: Application to Atmospheric Cosmic-Ray Showers Poster

Alexander Shen · Ann Lee · Luca Masserano · tommaso dorigo · Michele Doro · Rafael Izbicki

Rare Galaxy Classes Identified In Foundation Model Representations Poster

Mike Walmsley · Anna Scaife

Understanding and Visualizing Droplet Distributions in Simulations of Shallow Clouds Poster

Justus C. Will · Andrea Jenney · Kara Lamb · Mike Pritchard · Colleen Kaul · Po-Lun Ma · Jacob Shpund · Kyle Pressel · Marcus van Lier-Walqui · Stephan Mandt

Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e Poster

Jerry Yao-Chieh Hu · Chenwei Xu · Aakaash Narayanan · Mattson Thieme · Vladimir Nagaslaev · Mark Austin · Jeremy Arnold · Jose Berlioz · Pierrick Hanlet · Aisha Ibrahim · Dennis Nicklaus · Jovan Mitrevski · Gauri Pradhan · Andrea Saewert · Kiyomi Seiya · Brian Schupbach · Randy Thurman-Keup · Nhan Tran · Rui Shi · Seda Ogrenci · Alexis Maya-Isabelle Shuping · Kyle Hazelwood · Han Liu

Loss Functionals for Learning Likelihood Ratios Poster

Shahzar Rizvi · Mariel Pettee · Benjamin Nachman

19 Parameters Is All You Need: Tiny Neural Networks for Particle Physics Poster

Alexander Bogatskiy · Timothy Hoffman · Jan Offermann

CP-PINNs: Changepoints Detection in PDEs using Physics Informed Neural Networks with Total-Variation Penalty Poster

Zhikang Dong · Pawel Polak

Self-Driving Telescopes: Autonomous Scheduling of Astronomical Observation Campaigns with Offline Reinforcement Learning Poster

Franco Terranova · M Voetberg · Brian Nord · Amanda Pagul

High-dimensional and Permutation Invariant Anomaly Detection with Diffusion Generative Models Poster

Vinicius Mikuni · Benjamin Nachman

Generative Diffusion Models for Lattice Field Theory Poster

Lingxiao Wang · Gert Aarts · Kai Zhou

Reconstruction of Fields from Sparse Sensing: Differentiable Sensor Placement Enhances Generalization Poster

Agnese Marcato · Daniel O'Malley · Hari Viswanathan · Eric Guiltinan · Javier E. Santos

Learning Dark Matter Representation from Strong Lensing Images through Self-Supervision Poster

Yashwardhan Deshmukh · Kartik Sachdev · Michael Toomey · Sergei Gleyzer

Graph Neural Networks for Identifying Protein Reactive Compounds Poster

Victor Hugo Cano Gil · Christopher Rowley

Towards out-of-distribution generalization: robust networks learn similar representations Poster

Yash Gondhalekar · Sultan Hassan · Naomi Saphra · Sambatra Andrianomena

Towards an Astronomical Foundation Model for Stars Poster

Henry Leung

Induced Generative Adversarial Particle Transformers Poster

Anni Li · Venkat Krishnamohan · Raghav Kansal · Javier Duarte · Rounak Sen · Steven Tsan · Zhaoyu Zhang

Lensformer: A Physics-Informed Vision Transformer for Gravitational Lensing Poster

Lucas José Velôso de Souza · Michael Toomey · Sergei Gleyzer

Self-supervised learning for searching jellyfish galaxies in the ocean of data from upcoming surveys Poster

Yash Gondhalekar · Rafael de Souza · Ana Chies Santos · Carolina Queiroz

deep-REMAP: Parameterization of Stellar Spectra Using Regularized Multi-Task Learning Poster

Sankalp Gilda

Bayesian Simulation-based Inference for Cosmological Initial Conditions Poster

Noemi Anau Montel · Florian List · Christoph Weniger

Autoregressive Transformers for Disruption Prediction in Nuclear Fusion Plasmas Poster

Lucas Spangher · William Arnold · Alexander Spangher · Andrew Maris · Cristina Rea

CaloFFJORD: High Fidelity Calorimeter Simulation Using Continuous Normalizing Flows Poster

Chirag Furia · Vinicius Mikuni

Machine learning-assisted nanoscale photoelectrical sensing Poster

Ziyan Zhu · Zhurun (Judy) Ji · Houssam Yassin · Zhi-Xun Shen · Thomas Devereaux

Emulating deviations from Einstein's General Relativity using conditional GANs Poster

Yash Gondhalekar · Sownak Bose

Operator SVD with Neural Networks via Nested Low-Rank Approximation Poster

Jongha (Jon) Ryu · Xiangxiang Xu · Hasan Sabri Melihcan Erol · Yuheng Bu · Lizhong Zheng · Gregory Wornell

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Gradient weighted physics-informed neural networks for capturing shocks in porous media flows Poster

Somiya Kapoor · Abhishek Chandra · Taniya Kapoor · Mitrofan Curti

Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant Networks Poster

Favour Nerrise · Andrew Sosanya · Patrick Neary

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The DL Advocate: Playing the devil’s advocate with hidden systematic uncertainties Poster

Andrey Ustyuzhanin · Andrey Golutvin · Aleksandr Iniukhin · Patrick Owen · Andrea Mauri · Nicola Serra

MCMC to address model misspecification in Deep Learning classification of Radio Galaxies Poster

Devina Mohan · Anna Scaife

Application of Zone Method based Physics-Informed Neural Networks in Reheating Furnaces Poster

Ujjal Dutta · Aldo Lipani · Chuan Wang · Yukun Hu

LEO Satellite Orbit Prediction with Physics Informed Machine Learning Poster

Francesco Alesiani · Makoto Takamoto · Toshio Kamiya · Daisuke Etou

Physically Accurate Fast Nanophotonic Simulations with Physics Informed Model and Training Poster

Ahmet Onur Dasdemir · Can Dimici · Aykut Erdem · Emir Salih Magden

Bayesian Imaging for Radio Interferometry with Score-Based Priors Poster

Noé Dia · M. J. Yantovski-Barth · Alexandre Adam · Micah Bowles · Pablo Lemos · Laurence Perreault-Levasseur · Yashar Hezaveh · Anna Scaife

Virtual EVE: a Deep Learning Model for Solar Irradiance Prediction Poster

Manuel Indaco · Daniel Gass · William Fawcett · Richard Galvez · Paul Wright · Andres Munoz-Jaramillo

High-Cadence Thermospheric Density Estimation enabled by Machine Learning on Solar Imagery Poster

Shreshth Malik · James Edward Joseph Walsh · Giacomo Acciarini · Thomas Berger · Atilim Gunes Baydin

Combining astrophysical datasets with CRUMB Poster

Fiona Porter

Ultra Fast Transformers on FPGAs for Particle Physics Experiments Poster

Zhixing Jiang · Ziang Yin · Elham E Khoda · Vladimir Loncar · Ekaterina Govorkova · Eric Moreno · Philip Harris · Scott Hauck · Shih-chieh Hsu

Unleashing the Potential of Fractional Calculus in Graph Neural Networks Poster

Qiyu Kang · Kai Zhao · Qinxu Ding · Feng Ji · Xuhao Li · WENFEI LIANG · Yang Song · Wee Peng Tay

Approximately-invariant neural networks for quantum many-body physics Poster

Dominik Kufel · Jack Kemp · Norman Yao

Pseudotime Diffusion Poster

Jacob Moss · Jeremy England · Pietro Lió

Reinforcement Learning for Ising Model Poster

Yichen Lu · Xiao-Yang Liu

Reconstructing Free Energy Using Bayesian Thermodynamic Integration Poster

Alexander Lobashev · Mikhail Tamm

ELUQuant: Event-Level Uncertainty Quantification using Physics-Informed Bayesian Neural Networks with Flow approximated Posteriors - A DIS Study Poster

Cristiano Fanelli · James Giroux