Workshop
Machine Learning and the Physical Sciences
Atilim Gunes Baydin 路 Adji Bousso Dieng 路 Emine Kucukbenli 路 Gilles Louppe 路 Siddharth Mishra-Sharma 路 Benjamin Nachman 路 Brian Nord 路 Savannah Thais 路 Anima Anandkumar 路 Kyle Cranmer 路 Lenka Zdeborov谩 路 Rianne van den Berg
Room 275 - 277
Sat 3 Dec, 5:50 a.m. PST
The Machine Learning and the Physical Sciences workshop aims to provide an informal, inclusive and leading-edge venue for research and discussions at the interface of machine learning (ML) and the physical sciences. This interface spans (1) applications of ML in physical sciences (ML for physics), (2) developments in ML motivated by physical insights (physics for ML), and most recently (3) convergence of ML and physical sciences (physics with ML) which inspires questioning what scientific understanding means in the age of complex-AI powered science, and what roles machine and human scientists will play in developing scientific understanding in the future.
Chat is not available.
Timezone: America/Los_Angeles
Schedule
|
Sat 5:50 a.m. - 6:00 a.m.
|
Opening remarks
(
Introduction to the Workshop
)
>
SlidesLive Video |
馃敆 |
|
Sat 6:00 a.m. - 6:30 a.m.
|
Invited talk: David Pfau, "Deep Learning and Ab-Initio Quantum Chemistry and Materials"
(
Invited talk
)
>
SlidesLive Video |
David Pfau 路 Siddharth Mishra-Sharma 馃敆 |
|
Sat 6:30 a.m. - 6:45 a.m.
|
Contributed talk: Kieran Murphy, "Characterizing information loss in a chaotic double pendulum with the Information Bottleneck"
(
Contributed talk
)
>
SlidesLive Video |
Kieran Murphy 路 Siddharth Mishra-Sharma 馃敆 |
|
Sat 6:45 a.m. - 7:15 a.m.
|
Invited talk: Hiranya Peiris, "Prospects for understanding the physics of the Universe"
(
Invited talk
)
>
SlidesLive Video |
Hiranya Peiris 路 Siddharth Mishra-Sharma 馃敆 |
|
Sat 7:15 a.m. - 7:30 a.m.
|
Contributed talk: Marco Aversa, "Physical Data Models in Machine Learning Imaging Pipelines"
(
Contributed talk
)
>
SlidesLive Video |
Marco Aversa 路 Siddharth Mishra-Sharma 馃敆 |
|
Sat 7:30 a.m. - 8:00 a.m.
|
Invited Talk: Giorgio Parisi
(
Invited talk
)
>
SlidesLive Video |
馃敆 |
|
Sat 8:00 a.m. - 9:00 a.m.
|
Poster session 1 and break ( Poster session and break ) > link | 馃敆 |
|
Sat 9:00 a.m. - 10:00 a.m.
|
Panel: Kathleen Creel, Mario Krenn, and Emily Sullivan, "Philosophy of Science in the AI Era"
(
Panel
)
>
SlidesLive Video |
馃敆 |
|
Sat 10:00 a.m. - 11:15 a.m.
|
Lunch
(
Lunch
)
>
|
馃敆 |
|
Sat 11:15 a.m. - 11:45 a.m.
|
Invited talk: E. Do臒u艧 脟ubuk, "Scaling up material discovery via deep learning"
(
Invited talk
)
>
SlidesLive Video |
Ekin Dogus Cubuk 路 Siddharth Mishra-Sharma 馃敆 |
|
Sat 11:45 a.m. - 12:15 p.m.
|
Invited talk: Vinicius Mikuni, "Collider Physics Innovations Powered by Machine Learning"
(
Invited talk
)
>
SlidesLive Video |
Vinicius Mikuni 路 Siddharth Mishra-Sharma 馃敆 |
|
Sat 12:15 p.m. - 12:30 p.m.
|
Contributed talk: Aur茅lien Dersy, "Simplifying Polylogarithms with Machine Learning"
(
Contributed talk
)
>
SlidesLive Video |
Aurelien Dersy 路 Siddharth Mishra-Sharma 馃敆 |
|
Sat 12:30 p.m. - 1:00 p.m.
|
Invited talk: Federico Felici, "Magnetic control of tokamak plasmas through Deep Reinforcement Learning"
(
Invited talk
)
>
SlidesLive Video |
Federico Felici 路 Siddharth Mishra-Sharma 馃敆 |
|
Sat 1:00 p.m. - 1:15 p.m.
|
Contributed talk: Alexandre Adam, "Posterior samples of source galaxies in strong gravitational lenses with score-based priors"
(
Contributed talk
)
>
SlidesLive Video |
Alexandre Adam 路 Siddharth Mishra-Sharma 馃敆 |
|
Sat 1:15 p.m. - 1:30 p.m.
|
Break
|
馃敆 |
|
Sat 1:30 p.m. - 2:00 p.m.
|
Invited talk: Catherine Nakalembe and Hannah Kerner
(
Invited talk
)
>
SlidesLive Video |
Catherine Nakalembe 路 Hannah Kerner 路 Siddharth Mishra-Sharma 馃敆 |
|
Sat 2:00 p.m. - 2:05 p.m.
|
Closing remarks
(
Closing remarks
)
>
|
馃敆 |
|
Sat 2:05 p.m. - 3:00 p.m.
|
Poster session 2 ( Poster session ) > link | 馃敆 |
|
-
|
Leveraging the Stochastic Predictions of Bayesian Neural Networks for Fluid Simulations
(
Poster
)
>
|
Maximilian Mueller 路 Robin Greif 路 Frank Jenko 路 Nils Thuerey 馃敆 |
|
-
|
Discovering Long-period Exoplanets using Deep Learning with Citizen Science Labels
(
Poster
)
>
|
Shreshth A Malik 路 Nora Eisner 路 Chris Lintott 路 Yarin Gal 馃敆 |
|
-
|
HIGlow: Conditional Normalizing Flows for High-Fidelity HI Map Modeling
(
Poster
)
>
|
Roy Friedman 路 Sultan Hassan 馃敆 |
|
-
|
Virgo: Scalable Unsupervised Classification of Cosmological Shock Waves
(
Poster
)
>
|
Max Lamparth 路 Ludwig B枚ss 路 Ulrich Steinwandel 路 Klaus Dolag 馃敆 |
|
-
|
Learning Feynman Diagrams using Graph Neural Networks
(
Poster
)
>
|
Alexander Norcliffe 路 Harrison Mitchell 路 Pietro Li贸 馃敆 |
|
-
|
Certified data-driven physics-informed greedy auto-encoder simulator
(
Poster
)
>
|
Xiaolong He 路 Youngsoo Choi 路 William Fries 路 Jon Belof 路 Jiun-Shyan Chen 馃敆 |
|
-
|
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian Inference
(
Poster
)
>
|
Som Dhulipala 路 Yifeng Che 路 Michael Shields 馃敆 |
|
-
|
Offline Model-Based Reinforcement Learning for Tokamak Control
(
Poster
)
>
|
11 presentersIan Char 路 Joseph Abbate 路 Laszlo Bardoczi 路 Mark Boyer 路 Youngseog Chung 路 Rory Conlin 路 Keith Erickson 路 Viraj Mehta 路 Nathan Richner 路 Egemen Kolemen 路 Jeff Schneider |
|
-
|
Decay-aware neural network for event classification in collider physics
(
Poster
)
>
|
Tomoe Kishimoto 路 Masahiro Morinaga 路 Masahiko Saito 路 Junichi Tanaka 馃敆 |
|
-
|
Phase transitions and structure formation in learning local rules
(
Poster
)
>
|
Bojan 沤unkovi膷 路 Enej Ilievski 馃敆 |
|
-
|
Lyapunov Regularized Forecaster
(
Poster
)
>
|
Rong Zheng 路 Rose Yu 馃敆 |
|
-
|
Ad-hoc Pulse Shape Simulation using Cyclic Positional U-Net
(
Poster
)
>
|
Aobo Li 馃敆 |
|
-
|
Learning Uncertainties the Frequentist Way: Calibration and Correlation in High Energy Physics
(
Poster
)
>
|
Rikab Gambhir 路 Jesse Thaler 路 Benjamin Nachman 馃敆 |
|
-
|
Molecular Fingerprints for Robust and Efficient ML-Driven Molecular Generation
(
Poster
)
>
|
Ruslan Tazhigulov 路 Joshua Schiller 路 Jacob Oppenheim 路 Max Winston 馃敆 |
|
-
|
Machine Learning for Chemical Reactions \\A Dance of Datasets and Models
(
Poster
)
>
|
Mathias Schreiner 路 Arghya Bhowmik 路 Tejs Vegge 路 Jonas Busk 路 Peter Bj酶rn J酶rgensen 路 Ole Winther 馃敆 |
|
-
|
ML4LM: Machine Learning for Safely Landing on Mars
(
Poster
)
>
|
David Wu 路 Wai Tong Chung 路 Matthias Ihme 馃敆 |
|
-
|
Flexible learning of quantum states with generative query neural networks
(
Poster
)
>
|
Yan Zhu 路 Ya-Dong Wu 路 Ge Bai 路 Dong-Sheng Wang 路 Yuexuan Wang 路 Giulio Chiribella 馃敆 |
|
-
|
Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows
(
Poster
)
>
|
Raphael Pellegrin 路 Blake Bullwinkel 路 Marios Mattheakis 路 Pavlos Protopapas 馃敆 |
|
-
|
Decorrelation with Conditional Normalizing Flows
(
Poster
)
>
|
Samuel Klein 路 Tobias Golling 馃敆 |
|
-
|
A New Task: Deriving Semantic Class Targets for the Physical Sciences
(
Poster
)
>
|
Micah Bowles 馃敆 |
|
-
|
Machine-learned climate model corrections from a global storm-resolving model
(
Poster
)
>
|
Anna Kwa 馃敆 |
|
-
|
Amortized Bayesian Inference for Supernovae in the Era of the Vera Rubin Observatory Using Normalizing Flows
(
Poster
)
>
|
Victoria Villar 馃敆 |
|
-
|
Scalable Bayesian Inference for Finding Strong Gravitational Lenses
(
Poster
)
>
|
Yash Patel 路 Jeffrey Regier 馃敆 |
|
-
|
Training physical networks like neural networks: deep physical neural networks
(
Poster
)
>
|
Logan Wright 路 Tatsuhiro Onodera 路 Martin M Stein 路 Tianyu Wang 路 Darren Schachter 路 Zoey Hu 路 Peter McMahon 馃敆 |
|
-
|
A Curriculum-Training-Based Strategy for Distributing Collocation Points during Physics-Informed Neural Network Training
(
Poster
)
>
|
Marcus M眉nzer 路 Christopher Bard 馃敆 |
|
-
|
Learning latent variable evolution for the functional renormalization group
(
Poster
)
>
|
Matija Medvidovi膰 路 Alessandro Toschi 路 Giorgio Sangiovanni 路 Cesare Franchini 路 Andy Millis 路 Anirvan Sengupta 路 Domenico Di Sante 馃敆 |
|
-
|
Deformations of Boltzmann Distributions
(
Poster
)
>
|
B谩lint M谩t茅 路 Fran莽ois Fleuret 馃敆 |
|
-
|
Neuro-Symbolic Partial Differential Equation Solver
(
Poster
)
>
|
Pouria Akbari Mistani 路 Samira Pakravan 路 Rajesh Ilango 路 Sanjay Choudhry 路 Frederic Gibou 馃敆 |
|
-
|
Generating astronomical spectra from photometry with conditional diffusion models
(
Poster
)
>
|
Lars Doorenbos 路 Stefano Cavuoti 路 Giuseppe Longo 路 Massimo Brescia 路 Raphael Sznitman 路 Pablo M谩rquez Neila 馃敆 |
|
-
|
Identifying AGN host galaxies with convolutional neural networks
(
Poster
)
>
|
Ziting Guo 路 John Wu 路 Chelsea Sharon 馃敆 |
|
-
|
Efficiently Moving Instead of Reweighting Collider Events with Machine Learning
(
Poster
)
>
|
Radha Mastandrea 路 Benjamin Nachman 馃敆 |
|
-
|
D-optimal neural exploration of nonlinear physical systems
(
Poster
)
>
|
Matthieu Blanke 路 marc lelarge 馃敆 |
|
-
|
Machine learning for complete intersection Calabi-Yau manifolds
(
Poster
)
>
|
Harold Erbin 路 Mohamed Tamaazousti 路 Riccardo Finotello 馃敆 |
|
-
|
SuNeRF: Validation of a 3D Global Reconstruction of the Solar Corona Using Simulated EUV Images
(
Poster
)
>
|
11 presentersKyriaki-Margarita Bintsi 路 Robert Jarolim 路 Benoit Tremblay 路 Miraflor Santos 路 Anna Jungbluth 路 James Mason 路 Sairam Sundaresan 路 Angelos Vourlidas 路 Cooper Downs 路 Ronald Caplan 路 Andres Munoz-Jaramillo |
|
-
|
Generating Calorimeter Showers as Point Clouds
(
Poster
)
>
|
Simon Schnake 路 Dirk Kr眉cker 路 Kerstin Borras 馃敆 |
|
-
|
Physics solutions for privacy leaks in machine learning
(
Poster
)
>
|
Alejandro Pozas-Kerstjens 路 Senaida Hernandez-Santana 路 Jos茅 Ram贸n Pareja Monturiol 路 Marco Castrillon Lopez 路 Giannicola Scarpa 路 Carlos E. Gonzalez-Guillen 路 David Perez-Garcia 馃敆 |
|
-
|
From Particles to Fluids: Dimensionality Reduction for Non-Maxwellian Plasma Velocity Distributions Validated in the Fluid Context
(
Poster
)
>
|
Daniel da Silva 馃敆 |
|
-
|
Simplifying Polylogarithms with Machine Learning
(
Poster
)
>
|
Aurelien Dersy 路 Matthew Schwartz 路 Xiaoyuan Zhang 馃敆 |
|
-
|
NLP Inspired Training Mechanics For Modeling Transient Dynamics
(
Poster
)
>
|
Lalit Ghule 路 Rishikesh Ranade 路 Jay Pathak 馃敆 |
|
-
|
Neural Network-based Real-Time Parameter Estimation in Electrochemical Sensors with Unknown Confounding Factors
(
Poster
)
>
|
Sarthak Jariwala 馃敆 |
|
-
|
Learning dynamical systems: an example from open quantum system dynamics.
(
Poster
)
>
|
Pietro Novelli 馃敆 |
|
-
|
Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators
(
Poster
)
>
|
Jenna A Bilbrey 路 Kristina Herman 路 Henry Sprueill 路 Sotiris Xantheas 路 Payel Das 路 Manuel Lopez Roldan 路 Mike Kraus 路 Hatem Helal 路 Sutanay Choudhury 馃敆 |
|
-
|
Emulating Fast Processes in Climate Models
(
Poster
)
>
|
Noah Brenowitz 路 W. Andre Perkins 路 Jacqueline M. Nugent 路 Oliver Watt-Meyer 路 Spencer K. Clark 路 Anna Kwa 路 Brian Henn 路 Jeremy McGibbon 路 Christopher S. Bretherton 馃敆 |
|
-
|
GAUCHE: A Library for Gaussian Processes in Chemistry
(
Poster
)
>
|
18 presentersRyan-Rhys Griffiths 路 Leo Klarner 路 Henry Moss 路 Aditya Ravuri 路 Sang Truong 路 Bojana Rankovic 路 Yuanqi Du 路 Arian Jamasb 路 Julius Schwartz 路 Austin Tripp 路 Gregory Kell 路 Anthony Bourached 路 Alex Chan 路 Jacob Moss 路 Chengzhi Guo 路 Alpha Lee 路 Philippe Schwaller 路 Jian Tang |
|
-
|
One-shot learning for solution operators of partial differential equations
(
Poster
)
>
|
Lu Lu 路 Anran Jiao 路 Jay Pathak 路 Rishikesh Ranade 路 Haiyang He 馃敆 |
|
-
|
Wavelets Beat Monkeys at Adversarial Robustness
(
Poster
)
>
|
Jingtong Su 路 Julia Kempe 馃敆 |
|
-
|
Qubit seriation: Undoing data shuffling using spectral ordering
(
Poster
)
>
|
Atithi Acharya 路 Manuel Rudolph 路 Jing Chen 路 Jacob Miller 路 Alejandro Perdemo-Ortiz 馃敆 |
|
-
|
First principles physics-informed neural network for quantum wavefunctions and eigenvalue surfaces
(
Poster
)
>
|
Marios Mattheakis 路 Gabriel R. Schleder 路 Daniel Larson 路 Efthimios Kaxiras 馃敆 |
|
-
|
Clustering Behaviour of Physics-Informed Neural Networks: Inverse Modeling of An Idealized Ice Shelf
(
Poster
)
>
|
Yunona Iwasaki 路 Ching-Yao Lai 馃敆 |
|
-
|
Renormalization in the neural network-quantum field theory correspondence
(
Poster
)
>
|
Harold Erbin 路 Vincent Lahoche 路 Dine Ousmane Samary 馃敆 |
|
-
|
Applying Deep Reinforcement Learning to the HP Model for Protein Structure Prediction
(
Poster
)
>
|
Kaiyuan Yang 路 Houjing Huang 路 Olafs Vandans 路 Adithyavairavan Murali 路 Fujia Tian 路 Roland Yap 路 Liang Dai 馃敆 |
|
-
|
Intra-Event Aware Imitation Game for Fast Detector Simulation
(
Poster
)
>
|
Hosein Hashemi 路 Nikolai Hartmann 路 Sahand Sharifzadeh 路 James Kahn 路 Thomas Kuhr 馃敆 |
|
-
|
Deep Learning Modeling of Subgrid Physics in Cosmological N-body Simulations
(
Poster
)
>
|
Georgios Markos Chatziloizos 路 Francois Lanusse 路 Tristan Cazenave 馃敆 |
|
-
|
Combinational-convolution for flow-based sampling algorithm
(
Poster
)
>
|
Akio Tomiya 馃敆 |
|
-
|
Point Cloud Generation using Transformer Encoders and Normalising Flows
(
Poster
)
>
|
Benno K盲ch 路 Dirk Kr眉cker 路 Isabell Melzer 馃敆 |
|
-
|
Learning Similarity Metrics for Volumetric Simulations with Multiscale CNNs
(
Poster
)
>
|
Georg Kohl 路 Liwei Chen 路 Nils Thuerey 馃敆 |
|
-
|
Stabilization and Acceleration of CFD Simulation by Controlling Relaxation Factor Based on Residues: An SNN Based Approach
(
Poster
)
>
|
Sounak Dey 路 Dighanchal Banerjee 路 Mithilesh Maurya 路 Dilshad Ahmad 馃敆 |
|
-
|
Simulation-based inference of the 2D ex-situ stellar mass fraction distribution of galaxies using variational autoencoders
(
Poster
)
>
|
Eirini Angeloudi 路 Marc Huertas-Company 路 Jes煤s Falc贸n-Barroso 路 Regina Sarmiento 路 Daniel Walo-Mart铆n 路 Annalisa Pillepich 路 Jes煤s Vega Ferrero 馃敆 |
|
-
|
Uncertainty quantification methods for ML-based surrogate models of scientific applications
(
Poster
)
>
|
Kishore Basu 路 Yujia Hao 路 Delphine Hintz 路 Dev Shah 路 Aaron Palmer 路 Gurpreet Singh Hora 路 Darian Nwankwo 路 Laurent White 馃敆 |
|
-
|
Contrasting random and learned features in deep Bayesian linear regression
(
Poster
)
>
|
Jacob Zavatone-Veth 路 William Tong 路 Cengiz Pehlevan 馃敆 |
|
-
|
DS-GPS : A Deep Statistical Graph Poisson Solver (for faster CFD simulations)
(
Poster
)
>
|
Matthieu Nastorg 馃敆 |
|
-
|
Dynamical Mean Field Theory of Kernel Evolution in Wide Neural Networks
(
Poster
)
>
|
Blake Bordelon 路 Cengiz Pehlevan 馃敆 |
|
-
|
Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection
(
Poster
)
>
|
Aleksandra Ciprijanovic 路 Ashia Lewis 路 Kevin Pedro 路 Sandeep Madireddy 路 Brian Nord 路 Gabriel Nathan Perdue 路 Stefan Wild 馃敆 |
|
-
|
A Neural Network Subgrid Model of the Early Stages of Planet Formation
(
Poster
)
>
|
Thomas Pfeil 路 Miles Cranmer 路 Shirley Ho 路 Philip Armitage 路 Tilman Birnstiel 路 Hubert Klahr 馃敆 |
|
-
|
Validation Diagnostics for SBI algorithms based on Normalizing Flows
(
Poster
)
>
|
Julia Linhart 路 Alexandre Gramfort 路 Pedro Rodrigues 馃敆 |
|
-
|
One Network to Approximate Them All: Amortized Variational Inference of Ising Ground States
(
Poster
)
>
|
Sebastian Sanokowski 路 Wilhelm Berghammer 路 Johannes Kofler 路 Sepp Hochreiter 路 Sebastian Lehner 馃敆 |
|
-
|
Hybrid integration of the gravitational N-body problem with Artificial Neural Networks
(
Poster
)
>
|
Veronica Saz Ulibarrena 路 Simon Portegies Zwart 路 Elena Sellentin 路 Barry Koren 路 Philipp Horn 路 Maxwell X. Cai 馃敆 |
|
-
|
CAPE: Channel-Attention-Based PDE Parameter Embeddings for SciML
(
Poster
)
>
|
Makoto Takamoto 路 Francesco Alesiani 路 Mathias Niepert 馃敆 |
|
-
|
Real-time Health Monitoring of Heat Exchangers using Hypernetworks and PINNs
(
Poster
)
>
|
Ritam Majumdar 路 Vishal Jadhav 路 Anirudh Deodhar 路 Shirish Karande 路 Lovekesh Vig 路 Venkataramana Runkana 馃敆 |
|
-
|
Physics-Informed CNNs for Super-Resolution of Sparse Observations on Dynamical Systems
(
Poster
)
>
|
Daniel Kelshaw 路 Georgios Rigas 路 Luca Magri 馃敆 |
|
-
|
Neural Inference of Gaussian Processes for Time Series Data of Quasars
(
Poster
)
>
|
Egor Danilov 路 Aleksandra Ciprijanovic 路 Brian Nord 馃敆 |
|
-
|
Deep Learning-Based Spatiotemporal Multi-Event Reconstruction for Delay-Line Detectors
(
Poster
)
>
|
Marco Knipfer 路 Sergei Gleyzer 路 Stefan Meier 路 Jonas Heimerl 路 Peter Hommelhoff 馃敆 |
|
-
|
Tensor networks for active inference with discrete observation spaces
(
Poster
)
>
|
Samuel T. Wauthier 路 Bram Vanhecke 路 Tim Verbelen 路 Bart Dhoedt 馃敆 |
|
-
|
Employing CycleGANs to Generate Realistic STEM Images for Machine Learning
(
Poster
)
>
|
Abid Khan 路 Chia-Hao Lee 路 Pinshane Y. Huang 路 Bryan Clark 馃敆 |
|
-
|
HubbardNet: Efficient Predictions of the Bose-Hubbard Model Spectrum with Deep Neural Networks
(
Poster
)
>
|
Ziyan Zhu 路 Marios Mattheakis 路 Weiwei Pan 路 Efthimios Kaxiras 馃敆 |
|
-
|
Strong-Lensing Source Reconstruction with Denoising Diffusion Restoration Models
(
Poster
)
>
|
Konstantin Karchev 路 Noemi Anau Montel 路 Adam Coogan 路 Christoph Weniger 馃敆 |
|
-
|
Score-based Seismic Inverse Problems
(
Poster
)
>
|
Sriram Ravula 路 Dimitri Voytan 路 Elad Liebman 路 Ram Tuvi 路 Yash Gandhi 路 Hamza Ghani 路 Alex Ardel 路 Mrinal Sen 路 Alex Dimakis 馃敆 |
|
-
|
Deep-pretrained-FWI: combining supervised learning with physics-informed neural network
(
Poster
)
>
|
ANA PAULA MULLER 路 Clecio Roque Bom 路 Jess茅 Carvalho Costa 路 Elis芒ngela Lopes Faria 路 Marcelo Portes de Albuquerque 路 Marcio Portes de Albuquerque 馃敆 |
|
-
|
Differentiable composition for model discovery
(
Poster
)
>
|
Omer Rochman Sharabi 路 Gilles Louppe 馃敆 |
|
-
|
Improving Generalization with Physical Equations
(
Poster
)
>
|
Antoine Wehenkel 路 Jens Behrmann 路 Hsiang Hsu 路 Guillermo Sapiro 路 Gilles Louppe 路 Joern-Henrik Jacobsen 馃敆 |
|
-
|
Neural Fields for Fast and Scalable Interpolation of Geophysical Ocean Variables
(
Poster
)
>
|
Juan Emmanuel Johnson 路 Redouane Lguensat 路 ronan fablet 路 Emmanuel Cosme 路 Julien Le Sommer 馃敆 |
|
-
|
Interpretable Encoding of Galaxy Spectra
(
Poster
)
>
|
Yan Liang 路 Peter Melchior 路 Sicong Lu 馃敆 |
|
-
|
Neural Network Prior Mean for Particle Accelerator Injector Tuning
(
Poster
)
>
|
Connie Xu 路 Ryan Roussel 路 Auralee Edelen 馃敆 |
|
-
|
Applications of Differentiable Physics Simulations in Particle Accelerator Modeling
(
Poster
)
>
|
Ryan Roussel 路 Auralee Edelen 馃敆 |
|
-
|
A robust estimator of mutual information for deep learning interpretability
(
Poster
)
>
|
Davide Piras 路 Hiranya Peiris 路 Andrew Pontzen 路 Luisa Lucie-Smith 路 Brian Nord 路 Ningyuan (Lillian) Guo 馃敆 |
|
-
|
Finding NEEMo: Geometric Fitting using Neural Estimation of the Energy Mover鈥檚 Distance
(
Poster
)
>
|
Ouail Kitouni 路 Mike Williams 路 Niklas S Nolte 馃敆 |
|
-
|
DIGS: Deep Inference of Galaxy Spectra with Neural Posterior Estimation
(
Poster
)
>
|
Gourav Khullar 路 Brian Nord 路 Aleksandra Ciprijanovic 路 Jason Poh 路 Fei Xu 路 Ashwin Samudre 馃敆 |
|
-
|
Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference
(
Poster
)
>
|
Jason Poh 路 Ashwin Samudre 路 Aleksandra Ciprijanovic 路 Brian Nord 路 Joshua Frieman 路 Gourav Khullar 馃敆 |
|
-
|
Closing the resolution gap in Lyman alpha simulations with deep learning
(
Poster
)
>
|
Cooper Jacobus 路 Peter Harrington 路 Zarija Luki膰 馃敆 |
|
-
|
Physics-Informed Convolutional Neural Networks for Corruption Removal on Dynamical Systems
(
Poster
)
>
|
Daniel Kelshaw 路 Luca Magri 馃敆 |
|
-
|
Do graph neural networks learn jet substructure?
(
Poster
)
>
|
Farouk Mokhtar 路 Raghav Kansal 路 Javier Duarte 馃敆 |
|
-
|
Thermophysical Change Detection on the Moon with the Lunar Reconnaissance Orbiter Diviner sensor
(
Poster
)
>
|
Jose Delgado-Centeno 路 Silvia Bucci 路 Ziyi Liang 路 Ben Gaffinet 路 Valentin T. Bickel 路 Ben Moseley 路 Miguel Olivares 馃敆 |
|
-
|
Source Identification and Field Reconstruction of Advection-Diffusion Process from Sparse Sensor Measurements
(
Poster
)
>
|
Arka Daw 路 Kyongmin Yeo 路 Anuj Karpatne 路 馃敆 |
|
-
|
Geometry-aware Autoregressive Models for Calorimeter Shower Simulations
(
Poster
)
>
|
Junze Liu 路 Aishik Ghosh 路 Dylan Smith 路 Pierre Baldi 路 Daniel Whiteson 馃敆 |
|
-
|
Characterizing information loss in a chaotic double pendulum with the Information Bottleneck
(
Poster
)
>
|
Kieran Murphy 路 Danielle S Bassett 馃敆 |
|
-
|
Detecting structured signals in radio telescope data using RKHS
(
Poster
)
>
|
Russell Tsuchida 路 Suk Yee Yong 馃敆 |
|
-
|
Statistical Inference for Coadded Astronomical Images
(
Poster
)
>
|
Mallory Wang 路 Ismael Mendoza 路 Jeffrey Regier 路 Camille Avestruz 路 Cheng Wang 馃敆 |
|
-
|
Domain Adaptation for Simulation-Based Dark Matter Searches with Strong Gravitational Lensing
(
Poster
)
>
|
Pranath Reddy Kumbam 路 Sergei Gleyzer 路 Michael Toomey 路 Marcos Tidball 馃敆 |
|
-
|
A hybrid Reduced Basis and Machine-Learning algorithm for building Surrogate Models: a first application to electromagnetism
(
Poster
)
>
|
Alejandro Ribes 路 Ruben Persicot 路 Lucas Meyer 路 Jean-Pierre Ducreux 馃敆 |
|
-
|
Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian
(
Poster
)
>
|
Oswin So 路 Gongjie Li 路 Evangelos Theodorou 路 Molei Tao 馃敆 |
|
-
|
Deconvolving Detector Effects for Distribution Moments
(
Poster
)
>
|
Krish Desai 路 Benjamin Nachman 路 Jesse Thaler 馃敆 |
|
-
|
Multi-scale Digital Twin: Developing a fast and physics-infused surrogate model for groundwater contamination with uncertain climate models
(
Poster
)
>
|
Lijing Wang 路 Takuya Kurihana 路 Aurelien Meray 路 Ilijana Mastilovic 路 Satyarth Praveen 路 Zexuan Xu 路 Milad Memarzadeh 路 Alexander Lavin 路 Haruko Wainwright 馃敆 |
|
-
|
Topological Jet Tagging
(
Poster
)
>
|
Dawson Thomas 路 Sarah Demers 路 Smita Krishnaswamy 路 Bastian Rieck 馃敆 |
|
-
|
Physics-Driven Convolutional Autoencoder Approach for CFD Data Compressions
(
Poster
)
>
|
Alberto Olmo 路 Ahmed Zamzam 路 Andrew Glaws 路 Ryan King 馃敆 |
|
-
|
Recovering Galaxy Cluster Convergence from Lensed CMB with Generative Adversarial Networks
(
Poster
)
>
|
Liam Parker 路 Dongwon Han 路 Shirley Ho 路 Pablo Lemos 馃敆 |
|
-
|
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
(
Poster
)
>
|
Gabriele Corso 路 Hannes St盲rk 路 Bowen Jing 路 Regina Barzilay 路 Tommi Jaakkola 馃敆 |
|
-
|
Normalizing Flows for Fragmentation and Hadronization
(
Poster
)
>
|
Ahmed Youssef 路 Philip Ilten 路 Tony Menzo 路 Jure Zupan 路 Manuel Szewc 路 Stephen Mrenna 路 Michael K. Wilkinson 馃敆 |
|
-
|
Astronomical Image Coaddition with Bundle-Adjusting Radiance Fields
(
Poster
)
>
|
Harlan Hutton 路 Harshitha Palegar 路 Shirley Ho 路 Miles Cranmer 路 Peter Melchior 路 Jenna Eubank 馃敆 |
|
-
|
Differentiable Physics-based Greenhouse Simulation
(
Poster
)
>
|
Nhat M. Nguyen 路 Hieu Tran 路 Minh Duong 路 Hanh Bui 路 Kenneth Tran 馃敆 |
|
-
|
Plausible Adversarial Attacks on Direct Parameter Inference Models in Astrophysics
(
Poster
)
>
|
Benjamin Horowitz 路 Peter Melchior 馃敆 |
|
-
|
GAN-Flow: A dimension-reduced variational framework for physics-based inverse problems
(
Poster
)
>
|
Agnimitra Dasgupta 路 Dhruv Patel 路 Deep Ray 路 Erik Johnson 路 Assad Oberai 馃敆 |
|
-
|
Control and Calibration of GlueX Central Drift Chamber Using Gaussian Process Regression
(
Poster
)
>
|
Diana McSpadden 路 Torri Jeske 路 Naomi Jarvis 路 David Lawrence 路 Thomas Britton 路 nikhil kalra 馃敆 |
|
-
|
Emulating cosmological growth functions with B-Splines
(
Poster
)
>
|
Ngai Pok Kwan 路 Chirag Modi 路 Yin Li 路 Shirley Ho 馃敆 |
|
-
|
ClimFormer - a Spherical Transformer model for long-term climate projections
(
Poster
)
>
|
Salva R眉hling Cachay 路 Peetak Mitra 路 Sookyung Kim 路 Subhashis Hazarika 路 Haruki Hirasawa 路 Dipti Hingmire 路 Hansi Singh 路 Kalai Ramea 馃敆 |
|
-
|
Computing the Bayes-optimal classifier and exact maximum likelihood estimator with a semi-realistic generative model for jet physics
(
Poster
)
>
|
Kyle Cranmer 路 Matthew Drnevich 路 Lauren Greenspan 路 Sebastian Macaluso 路 Duccio Pappadopulo 馃敆 |
|
-
|
The Senseiver: attention-based global field reconstruction from sparse observations
(
Poster
)
>
|
Javier E. Santos 路 Zachary Fox 路 Arvind Mohan 路 Hari Viswanathan 路 NIcholas Lubbers 馃敆 |
|
-
|
SE(3)-equivariant self-attention via invariant features
(
Poster
)
>
|
Nan Chen 路 Soledad Villar 馃敆 |
|
-
|
Skip Connections for High Precision Regressors
(
Poster
)
>
|
Ayan Paul 路 Fady Bishara 路 Jennifer Dy 馃敆 |
|
-
|
Likelihood-Free Frequentist Inference for Calorimetric Muon Energy Measurement in High-Energy Physics
(
Poster
)
>
|
Luca Masserano 路 Ann Lee 路 Rafael Izbicki 路 Mikael Kuusela 路 tommaso dorigo 馃敆 |
|
-
|
Uncertainty Aware Deep Learning for Particle Accelerators
(
Poster
)
>
|
Kishansingh Rajput 路 Malachi Schram 路 Karthik Somayaji NS 馃敆 |
|
-
|
Graphical Models are All You Need: Per-interaction reconstruction uncertainties in a dark matter detection experiment
(
Poster
)
>
|
Christina Peters 路 Aaron Higuera 路 Shixiao Liang 路 Waheed Bajwa 路 Christopher Tunnell 馃敆 |
|
-
|
PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant Aggregator Network for Particle Physics
(
Poster
)
>
|
Jan Offermann 路 Alexander Bogatskiy 路 Timothy Hoffman 路 David W Miller 馃敆 |
|
-
|
FO-PINNs: A First-Order formulation for Physics~Informed Neural Networks
(
Poster
)
>
|
Rini Jasmine Gladstone 路 Mohammad Amin Nabian 路 Hadi Meidani 馃敆 |
|
-
|
Learning the nonlinear manifold of extreme aerodynamics
(
Poster
)
>
|
Kai Fukami 路 Kunihiko Taira 馃敆 |
|
-
|
Geometric NeuralPDE (GNPnet) Models for Learning Dynamics
(
Poster
)
>
|
Oluwadamilola Fasina 路 Smita Krishnaswamy 路 Aditi Krishnapriyan 馃敆 |
|
-
|
Can denoising diffusion probabilistic models generate realistic astrophysical fields?
(
Poster
)
>
|
Nayantara Mudur 路 Douglas P. Finkbeiner 馃敆 |
|
-
|
PIPS: Path Integral Stochastic Optimal Control for Path Sampling in Molecular Dynamics
(
Poster
)
>
|
Lars Holdijk 路 Yuanqi Du 路 Ferry Hooft 路 Priyank Jaini 路 Berend Ensing 路 Max Welling 馃敆 |
|
-
|
Predicting Full-Field Turbulent Flows Using Fourier Neural Operator
(
Poster
)
>
|
Peter Renn 路 Sahin Lale 路 Cong Wang 路 Zongyi Li 路 Anima Anandkumar 路 Morteza Gharib 馃敆 |
|
-
|
A Self-Supervised Approach to Reconstruction in Sparse X-Ray Computed Tomography
(
Poster
)
>
|
Rey Mendoza 路 Minh Nguyen 路 Judith Weng Zhu 路 Talita Perciano 路 Vincent Dumont 路 Juliane Mueller 路 Vidya Ganapati 馃敆 |
|
-
|
Energy based models for tomography of quantum spin-lattice systems
(
Poster
)
>
|
Abhijith Jayakumar 路 Marc Vuffray 路 Andrey Lokhov 馃敆 |
|
-
|
Elements of effective machine learning datasets in astronomy
(
Poster
)
>
|
Bernie Boscoe 路 Tuan Do 馃敆 |
|
-
|
Towards a non-Gaussian Generative Model of large-scale Reionization Maps
(
Poster
)
>
|
Yu-Heng Lin 路 Sultan Hassan 路 Bruno R茅galdo-Saint Blancard 路 Michael Eickenberg 路 Chirag Modi 馃敆 |
|
-
|
Adversarial Noise Injection for Learned Turbulence Simulations
(
Poster
)
>
|
Jingtong Su 路 Julia Kempe 路 Drummond Fielding 路 Nikolaos Tsilivis 路 Miles Cranmer 路 Shirley Ho 馃敆 |
|
-
|
Shining light on data
(
Poster
)
>
|
Akshat Kumar 路 Mohan Sarovar 馃敆 |
|
-
|
A Novel Automatic Mixed Precision Approach For Physics Informed Training
(
Poster
)
>
|
Jinze Xue 路 Akshay Subramaniam 路 Mark Hoemmen 馃敆 |
|
-
|
Atmospheric retrievals of exoplanets using learned parameterizations of pressure-temperature profiles
(
Poster
)
>
|
Timothy Gebhard 路 Daniel Angerhausen 路 Bj枚rn Konrad 路 Eleonora Alei 路 Sascha Quanz 路 Bernhard Sch枚lkopf 馃敆 |
|
-
|
Probabilistic Mixture Modeling For End-Member Extraction in Hyperspectral Data
(
Poster
)
>
|
Oliver Hoidn 路 Aashwin Mishra 路 Apurva Mehta 馃敆 |
|
-
|
Posterior samples of source galaxies in strong gravitational lenses with score-based priors
(
Poster
)
>
|
Alexandre Adam 路 Adam Coogan 路 Nikolay Malkin 路 Ronan Legin 路 Laurence Perreault-Levasseur 路 Yashar Hezaveh 路 Yoshua Bengio 馃敆 |
|
-
|
Particle-level Compression for New Physics Searches
(
Poster
)
>
|
Yifeng Huang 路 Jack Collins 路 Benjamin Nachman 路 Simon Knapen 路 Daniel Whiteson 馃敆 |
|
-
|
CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds
(
Poster
)
>
|
Jesse Cresswell 路 Brendan Ross 路 Gabriel Loaiza-Ganem 路 Humberto Reyes-Gonzalez 路 Marco Letizia 路 Anthony Caterini 馃敆 |
|
-
|
De-noising non-Gaussian fields in cosmology with normalizing flows
(
Poster
)
>
|
Adam Rouhiainen 路 Moritz M眉nchmeyer 馃敆 |
|
-
|
Learning Integrable Dynamics with Action-Angle Networks
(
Poster
)
>
|
Ameya Daigavane 路 Arthur Kosmala 路 Miles Cranmer 路 Tess Smidt 路 Shirley Ho 馃敆 |
|
-
|
Physics-informed Bayesian Optimization of an Electron Microscope
(
Poster
)
>
|
Desheng Ma 馃敆 |
|
-
|
Why are deep learning-based models of geophysical turbulence long-term unstable?
(
Poster
)
>
|
Ashesh Chattopadhyay 路 Pedram Hassanzadeh 馃敆 |
|
-
|
Graph Structure from Point Clouds: Geometric Attention is All You Need
(
Poster
)
>
|
Daniel Murnane 馃敆 |
|
-
|
One-Class Dense Networks for Anomaly Detection
(
Poster
)
>
|
Norman Karr 路 Benjamin Nachman 路 David Shih 馃敆 |
|
-
|
Self-supervised detection of atmospheric phenomena from remotely sensed synthetic aperture radar imagery
(
Poster
)
>
|
Yannik Glaser 路 Peter Sadowski 路 Justin Stopa 馃敆 |
|
-
|
Emulating cosmological multifields with generative adversarial networks
(
Poster
)
>
|
Sambatra Andrianomena 路 Sultan Hassan 路 Francisco Villaescusa-Navarro 馃敆 |
|
-
|
Monte Carlo Techniques for Addressing Large Errors and Missing Data in Simulation-based Inference
(
Poster
)
>
|
Bingjie Wang 路 Joel Leja 路 Victoria Villar 路 Joshua Speagle 馃敆 |
|
-
|
Towards Creating Benchmark Datasets of Universal Neural Network Potential for Material Discovery
(
Poster
)
>
|
So Takamoto 路 Chikashi Shinagawa 路 Nontawat Charoenphakdee 馃敆 |
|
-
|
Physics-informed neural networks for modeling rate- and temperature-dependent plasticity
(
Poster
)
>
|
Rajat Arora 路 Pratik Kakkar 路 Amit Chakraborty 路 Biswadip Dey 馃敆 |
|
-
|
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful
(
Poster
)
>
|
Joeri Hermans 路 Arnaud Delaunoy 路 Fran莽ois Rozet 路 Antoine Wehenkel 路 Volodimir Begy 路 Gilles Louppe 馃敆 |
|
-
|
Learning-based solutions to nonlinear hyperbolic PDEs: Empirical insights on generalization errors
(
Poster
)
>
|
Bilal Thonnam Thodi 路 Sai Venkata Ramana Ambadipudi 路 Saif Eddin Jabari 馃敆 |
|
-
|
Modeling halo and central galaxy orientations on the SO(3) manifold with score-based generative models
(
Poster
)
>
|
Yesukhei Jagvaral 路 Francois Lanusse 路 Rachel Mandelbaum 馃敆 |
|
-
|
Improved Training of Physics-informed Neural Networks using Energy-Based priors: A Study on Electrical Impedance Tomography
(
Poster
)
>
|
Akarsh Pokkunuru 路 Pedram Rooshenas 路 Thilo Strauss 路 Anuj Abhishek 路 Taufiquar Khan 馃敆 |
|
-
|
Geometric path augmentation for inference of sparsely observed stochastic nonlinear systems
(
Poster
)
>
|
Dimitra Maoutsa 馃敆 |
|
-
|
How good is the Standard Model? Machine learning multivariate Goodness of Fit tests
(
Poster
)
>
|
Gaia Grosso 路 Marco Letizia 路 Andrea Wulzer 路 Maurizio Pierini 馃敆 |
|
-
|
A probabilistic deep learning model to distinguish cusps and cores in dwarf galaxies
(
Poster
)
>
|
Julen Exp贸sito M谩rquez 路 Marc Huertas-Company 路 Arianna Di Cintio 路 Chris Brook 路 Andrea Macci貌 路 Rob Grant 路 Elena Arjona 馃敆 |
|
-
|
Super-resolving Dark Matter Halos using Generative Deep Learning
(
Poster
)
>
|
David Schaurecker 馃敆 |
|
-
|
Using Shadows to Learn Ground State Properties of Quantum Hamiltonians
(
Poster
)
>
|
Viet T. Tran 路 Laura Lewis 路 Johannes Kofler 路 Hsin-Yuan Huang 路 Richard Kueng 路 Sepp Hochreiter 路 Sebastian Lehner 馃敆 |
|
-
|
Set-Conditional Set Generation for Particle Physics
(
Poster
)
>
|
Sanmay Ganguly 路 Lukas Heinrich 路 Nilotpal Kakati 路 Nathalie Soybelman 馃敆 |
|
-
|
Score Matching via Differentiable Physics
(
Poster
)
>
|
Benjamin Holzschuh 路 Simona Vegetti 路 Nils Thuerey 馃敆 |
|
-
|
Adaptive Selection of Atomic Fingerprints for High-Dimensional Neural Network Potentials
(
Poster
)
>
|
Johannes Sandberg 路 Emilie Devijver 路 Noel Jakse 路 Thomas Voigtmann 馃敆 |
|
-
|
HyperFNO: Improving the Generalization Behavior of Fourier Neural Operators
(
Poster
)
>
|
Francesco Alesiani 路 Makoto Takamoto 路 Mathias Niepert 馃敆 |
|
-
|
Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study
(
Poster
)
>
|
David Ruhe 路 Kaze Wong 路 Miles Cranmer 路 Patrick Forr茅 馃敆 |
|
-
|
Fast kinematics modeling for conjunction with lens image modeling
(
Poster
)
>
|
Matthew Gomer 路 Luca Biggio 路 Sebastian Ertl 路 Han Wang 路 Aymeric Galan 路 Lyne Van de Vyvere 路 Dominique Sluse 路 Georgios Vernardos 路 Sherry Suyu 馃敆 |
|
-
|
Multi-Fidelity Transfer Learning for accurate database PDE approximation
(
Poster
)
>
|
Wenzhuo LIU 路 Mouadh Yagoubi 路 Marc Schoenauer 路 David Danan 馃敆 |
|
-
|
Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows
(
Poster
)
>
|
Anna Willmann 路 Jurjen Pieter Couperus Cabada臒 路 Yen-Yu Chang 路 Richard Pausch 路 Amin Ghaith 路 Alexander Debus 路 Arie Irman 路 Michael Bussmann 路 Ulrich Schramm 路 Nico Hoffmann 馃敆 |
|
-
|
Continual learning autoencoder training for a particle-in-cell simulation via streaming
(
Poster
)
>
|
Patrick Stiller 路 Varun Makdani 路 Franz Poeschel 路 Richard Pausch 路 Alexander Debus 路 Michael Bussmann 路 Nico Hoffmann 馃敆 |
|
-
|
On Using Deep Learning Proxies as Forward Models in Optimization Problems
(
Poster
)
>
|
Fatima Albreiki 路 Nidhal Belayouni 路 Deepak Gupta 馃敆 |
|
-
|
HGPflow: Particle reconstruction as hyperedge prediction
(
Poster
)
>
|
Etienne Dreyer 路 Nilotpal Kakati 路 Francesco Armando Di Bello 馃敆 |
|
-
|
Anomaly Detection with Multiple Reference Datasets in High Energy Physics
(
Poster
)
>
|
Mayee Chen 路 Benjamin Nachman 路 Frederic Sala 馃敆 |
|
-
|
Do Better QM9 Models Extrapolate as Better Quantum Chemical Property Predictors?
(
Poster
)
>
|
YUCHENG ZHANG 路 Nontawat Charoenphakdee 路 So Takamoto 馃敆 |
|
-
|
Diversity Balancing Generative Adversarial Networks for fast simulation of the Zero Degree Calorimeter in the ALICE experiment at CERN
(
Poster
)
>
|
Jan Dubi艅ski 路 Kamil Deja 路 Sandro Wenzel 路 Przemys艂aw Rokita 路 Tomasz Trzcinski 馃敆 |
|
-
|
Identifying Hamiltonian Manifold in Neural Networks
(
Poster
)
>
|
Yeongwoo Song 路 Hawoong Jeong 馃敆 |
|
-
|
Physics-Informed Neural Networks as Solvers for the Time-Dependent Schr枚dinger Equation
(
Poster
)
>
|
Karan Shah 路 Patrick Stiller 路 Nico Hoffmann 路 Attila Cangi 馃敆 |
|
-
|
Time-aware Bayesian optimization for adaptive particle accelerator tuning
(
Poster
)
>
|
Nikita Kuklev 路 Yine Sun 路 Hairong Shang 路 Michael Borland 路 Gregory Fystro 馃敆 |
|
-
|
Inferring molecular complexity from mass spectrometry data using machine learning
(
Poster
)
>
|
Timothy Gebhard 路 Aaron C. Bell 路 Jian Gong 路 Jaden J. A. Hastings 路 George Fricke 路 Nathalie Cabrol 路 Scott Sandford 路 Michael Phillips 路 Kimberley Warren-Rhodes 路 Atilim Gunes Baydin 馃敆 |
|
-
|
A physics-informed search for metric solutions to Ricci flow, their embeddings, and visualisation
(
Poster
)
>
|
Aarjav Jain 路 Challenger Mishra 路 Pietro Li贸 馃敆 |
|
-
|
Detection is truncation: studying source populations with truncated marginal neural ratio estimation
(
Poster
)
>
|
Noemi Anau Montel 路 Christoph Weniger 馃敆 |
|
-
|
Galaxy Morphological Classification with Deformable Attention Transformer
(
Poster
)
>
|
SEOKUN KANG 路 Min-Su Shin 路 Taehwan Kim 馃敆 |
|
-
|
Towards solving model bias in cosmic shear forward modeling
(
Poster
)
>
|
Benjamin Remy 路 Francois Lanusse 路 Jean-Luc Starck 馃敆 |
|
-
|
Physical Data Models in Machine Learning Imaging Pipelines
(
Poster
)
>
|
Marco Aversa 路 Luis Oala 路 Christoph Clausen 路 Roderick Murray-Smith 路 Bruno Sanguinetti 馃敆 |
|
-
|
Amortized Bayesian Inference of GISAXS Data with Normalizing Flows
(
Poster
)
>
|
Maksim Zhdanov 路 Lisa Randolph 路 Thomas Kluge 路 Motoaki Nakatsutsumi 路 Christian Gutt 路 Marina Ganeva 路 Nico Hoffmann 馃敆 |
|
-
|
Insight into cloud processes from unsupervised classification with a rotation-invariant autoencoder
(
Poster
)
>
|
Takuya Kurihana 路 James Franke 路 Ian Foster 路 Ziwei Wang 路 Elisabeth Moyer 馃敆 |
|
-
|
Addressing out-of-distribution data for flow-based gravitational wave inference
(
Poster
)
>
|
Maximilian Dax 路 Stephen Green 路 Jonas Wildberger 路 Jonathan Gair 路 Michael Puerrer 路 Jakob Macke 路 Alessandra Buonanno 路 Bernhard Sch枚lkopf 馃敆 |
|
-
|
A fast and flexible machine learning approach to data quality monitoring
(
Poster
)
>
|
Marco Letizia 路 Gaia Grosso 路 Andrea Wulzer 路 Marco Zanetti 路 Jacopo Pazzini 路 Marco Rando 路 Nicol貌 Lai 馃敆 |
|
-
|
Cosmology from Galaxy Redshift Surveys with PointNet
(
Poster
)
>
|
Sotiris Anagnostidis 路 Arne Thomsen 路 Alexandre Refregier 路 Tomasz Kacprzak 路 Luca Biggio 路 Thomas Hofmann 路 Tilman Tr枚ster 馃敆 |
|
-
|
Finding active galactic nuclei through Fink
(
Poster
)
>
|
Etienne Russeil 路 Emille Ishida 路 Julien Peloton 路 Anais M枚ller 路 Roman Le Montagner 馃敆 |