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45 Results
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Workshop
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Neuro-Symbolic Partial Differential Equation Solver Pouria Akbari Mistani · Samira Pakravan · Rajesh Ilango · Sanjay Choudhry · Frederic Gibou |
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Workshop
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One-shot learning for solution operators of partial differential equations Lu Lu · Anran Jiao · Jay Pathak · Rishikesh Ranade · Haiyang He |
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Poster
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Tue 9:00 |
A composable machine-learning approach for steady-state simulations on high-resolution grids Rishikesh Ranade · Chris Hill · Lalit Ghule · Jay Pathak |
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Poster
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Wed 9:00 |
Riemannian Neural SDE: Learning Stochastic Representations on Manifolds Sung Woo Park · Hyomin Kim · Kyungjae Lee · Junseok Kwon |
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Workshop
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Fourier Continuation for Exact Derivative Computation in Physics-Informed Neural Operators Haydn Maust · Zongyi Li · Yixuan Wang · Anima Anandkumar |
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Workshop
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Learning Ordinary Differential Equations with the Line Integral Loss Function Albert Johannessen |
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Poster
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Neural Stochastic Control Jingdong Zhang · Qunxi Zhu · Wei LIN |
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Poster
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Thu 14:00 |
Is Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? Chuwei Wang · Shanda Li · Di He · Liwei Wang |
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Poster
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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 |
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Poster
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Tue 9:00 |
Deep Generalized Schrödinger Bridge Guan-Horng Liu · Tianrong Chen · Oswin So · Evangelos Theodorou |
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Poster
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Tue 9:00 |
On the SDEs and Scaling Rules for Adaptive Gradient Algorithms Sadhika Malladi · Kaifeng Lyu · Abhishek Panigrahi · Sanjeev Arora |
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Poster
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Wed 14:00 |
Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations Andreas Besginow · Markus Lange-Hegermann |