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Poster
M2N: Mesh Movement Networks for PDE Solvers
Wenbin Song · Mingrui Zhang · Joseph G Wallwork · Junpeng Gao · Zheng Tian · Fanglei Sun · Matthew Piggott · Junqing Chen · Zuoqiang Shi · Xiang Chen · Jun Wang
Poster
Tue 9:00 On the SDEs and Scaling Rules for Adaptive Gradient Algorithms
Sadhika Malladi · Kaifeng Lyu · Abhishek Panigrahi · Sanjeev Arora
Poster
Tue 9:00 Deep Generalized Schrödinger Bridge
Guan-Horng Liu · Tianrong Chen · Oswin So · Evangelos Theodorou
Poster
Neural Stochastic Control
Jingdong Zhang · Qunxi Zhu · Wei LIN
Poster
Tue 9:00 A composable machine-learning approach for steady-state simulations on high-resolution grids
Rishikesh Ranade · Chris Hill · Lalit Ghule · Jay Pathak
Poster
Wed 9:00 Riemannian Neural SDE: Learning Stochastic Representations on Manifolds
Sung Woo Park · Hyomin Kim · Kyungjae Lee · Junseok Kwon
Poster
Thu 14:00 Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network?
Chuwei Wang · Shanda Li · Di He · Liwei Wang
Workshop
Fourier Continuation for Exact Derivative Computation in Physics-Informed Neural Operators
Haydn Maust · Zongyi Li · Yixuan Wang · Anima Anandkumar
Workshop
Learning Ordinary Differential Equations with the Line Integral Loss Function
Albert Johannessen
Workshop
Neuro-Symbolic Partial Differential Equation Solver
Pouria Akbari Mistani · Samira Pakravan · Rajesh Ilango · Sanjay Choudhry · Frederic Gibou
Workshop
One-shot learning for solution operators of partial differential equations
Lu Lu · Anran Jiao · Jay Pathak · Rishikesh Ranade · Haiyang He
Poster
Wed 14:00 Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules
Kazuki Irie · Francesco Faccio · Jürgen Schmidhuber