ICLR 2023 Workshop Physics4ML Submissions

Physics-based symbolic regression for power flow modeling and analysis
Anonymous
- 12 Feb 2023 (modified: 03 Mar 2023)
- Submitted to Physics4ML
- Readers: Everyone
A Critical Review on Machine Learning Applications in Sciences
Anonymous
- 09 Feb 2023 (modified: 03 Mar 2023)
- Submitted to Physics4ML
- Readers: Everyone
The END: An Equivariant Neural Decoder for Quantum Error Correction
Evgenii Egorov, Roberto Bondesan, Max Welling
- Published: 03 Mar 2023, Last Modified: 01 Apr 2023
- Physics4ML Poster
- Readers: Everyone
Cells Are Not Rectangles: A CNN Equivariant to the Symmetries of 2D Images of Things with Irregular Boundary
Anonymous
- 09 Feb 2023 (modified: 03 Mar 2023)
- Submitted to Physics4ML
- Readers: Everyone
Physics-driven machine learning models coupling PyTorch and Firedrake
Nacime Bouziani, David A Ham
- Published: 03 Mar 2023, Last Modified: 21 Apr 2024
- Physics4ML Poster
- Readers: Everyone
Estimation of acoustic field in 1-D duct using artificial neural networks
Anonymous
- 09 Feb 2023 (modified: 03 Mar 2023)
- Submitted to Physics4ML
- Readers: Everyone
E($3$) Equivariant Graph Neural Networks for Particle-Based Fluid Mechanics
Artur Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams
- Published: 03 Mar 2023, Last Modified: 23 Mar 2023
- Physics4ML Poster
- Readers: Everyone
$\mathrm{SE}(3)$ Frame Equivariance in Dynamics Modeling and Reinforcement Learning
Linfeng Zhao, Jung Yeon Park, Xupeng Zhu, Robin Walters, Lawson L.S. Wong
- Published: 03 Mar 2023, Last Modified: 03 Mar 2023
- Physics4ML Poster
- Readers: Everyone
Learned Gridification for Efficient Processing of Point Clouds
Anonymous
- 09 Feb 2023 (modified: 03 Mar 2023)
- Submitted to Physics4ML
- Readers: Everyone
Learning the Dynamics of Physical Systems with Hamiltonian Graph Neural Networks
Suresh Bishnoi, Ravinder Bhattoo, Jayadeva Jayadeva, Sayan Ranu, N M Anoop Krishnan
- Published: 03 Mar 2023, Last Modified: 31 Mar 2023
- Physics4ML Poster
- Readers: Everyone
Latent Sequence Generation of Steered Molecular Dynamics
John Kevin Cava, Ankita Shukla, John Wyatt Vant, Shubhra Kanti Karmaker, Pavan K. Turaga, Ross Maciejewski, Abhishek Singharoy
- Published: 03 Mar 2023, Last Modified: 31 Mar 2023
- Physics4ML Poster
- Readers: Everyone
Geometric constraints improve inference of sparsely observed stochastic dynamics
Dimitra Maoutsa
- Published: 03 Mar 2023, Last Modified: 01 Apr 2023
- Physics4ML Poster
- Readers: Everyone
Fast computation of permutation equivariant layers with the partition algebra
Charles Godfrey, Michael G. Rawson, Davis Brown, Henry Kvinge
- Published: 03 Mar 2023, Last Modified: 08 Mar 2023
- Physics4ML Poster
- Readers: Everyone
Predicting Fluid Dynamics in Physical-informed Mesh-reduced Space
Yeping Hu, Bo Lei, Victor M Castillo
- Published: 03 Mar 2023, Last Modified: 01 Apr 2023
- Physics4ML Poster
- Readers: Everyone
Scientific Computing Algorithms to Learn Enhanced Scalable Surrogates for Mesh Physics
Brian R. Bartoldson, Yeping Hu, Amar Saini, Jose Cadena, Yucheng Fu, Jie Bao, Zhijie Xu, Brenda Ng, Phan Nguyen
- Published: 03 Mar 2023, Last Modified: 03 Apr 2023
- Physics4ML Poster
- Readers: Everyone
Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties
Joshua Fagin, Ji Won Park, Henry Best, Matthew O'Dowd
- Published: 03 Mar 2023, Last Modified: 09 Apr 2023
- Physics4ML Spotlight
- Readers: Everyone
Multilevel Approach to Efficient Gradient Calculation in Stochastic Systems
Joohwan Ko, Michael Poli, Stefano Massaroli, Woo Chang Kim
- Published: 03 Mar 2023, Last Modified: 28 Mar 2023
- Physics4ML Poster
- Readers: Everyone
Studying Phase Transitions in Contrastive Learning With Physics-Inspired Datasets
Ali Cy, Anugrah Chemparathy, Michael Han, Rumen Dangovski, Peter Y. Lu, Marin Soljacic
- Published: 03 Mar 2023, Last Modified: 01 Apr 2023
- Physics4ML Poster
- Readers: Everyone
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak Kiani
- Published: 03 Mar 2023, Last Modified: 31 Mar 2023
- Physics4ML Poster
- Readers: Everyone
Lorentz Group Equivariant Autoencoders
Zichun Hao, Raghav Kansal, Javier Duarte, Nadya Chernyavskaya
- Published: 03 Mar 2023, Last Modified: 28 Mar 2023
- Physics4ML Poster
- Readers: Everyone
Relational Macrostate Theory Guides Artificial Intelligence to Learn Macro and Design Micro
Yanbo Zhang, Sara Walker
- Published: 03 Mar 2023, Last Modified: 15 Mar 2023
- Physics4ML Poster
- Readers: Everyone
Emulating Radiation Transport on Cosmological Scales using a Denoising U-Net
Mosima Masipa, Sultan Hassan, Mario Santos, Kyunghyun Cho, Gabriella Contardo
- Published: 03 Mar 2023, Last Modified: 13 Mar 2023
- Physics4ML Poster
- Readers: Everyone
Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement
Eden Saig, Nir Rosenfeld
- Published: 03 Mar 2023, Last Modified: 01 Apr 2023
- Physics4ML Poster
- Readers: Everyone
Learning protein family manifolds with smoothed energy-based models
Nathan C. Frey, Dan Berenberg, Joseph Kleinhenz, Isidro Hotzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi
- Published: 03 Mar 2023, Last Modified: 31 Mar 2023
- Physics4ML Spotlight
- Readers: Everyone
Nature's Cost Function: Simulating Physics by Minimizing the Action
Samuel James Greydanus, Timothy David Strang, Isabella Caruso
- Published: 03 Mar 2023, Last Modified: 21 Apr 2024
- Physics4ML Poster
- Readers: Everyone