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31 Results
Workshop
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Two-Step Bayesian PINNs for Uncertainty Estimation Pablo Flores · Olga Graf · Pavlos Protopapas · Karim Pichara |
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Workshop
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Sat 6:30 |
The Symbiosis of Deep Learning and Differential Equations -- III Luca Herranz-Celotti · Martin Magill · Ermal Rrapaj · Winnie Xu · Qiyao Wei · Archis Joglekar · Michael Poli · Animashree Anandkumar |
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Workshop
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Semi-Implicit Neural Ordinary Differential Equations for Learning Chaotic Systems Hong Zhang · Ying Liu · Romit Maulik |
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Workshop
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Attention-guided neural differential equations for physics-constrained deep learning of ion transport Danyal Rehman · John Lienhard |
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Workshop
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Sat 9:45 |
Can Physics informed Neural Operators self improve? Ritam Majumdar · Amey Varhade · Shirish Karande · Lovekesh Vig |
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Workshop
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Generalized One-Shot Transfer Learning of Linear Ordinary and Partial Differential Equations Pavlos Protopapas · Hari Raval |
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Poster
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Tue 15:15 |
Exploring the Optimal Choice for Generative Processes in Diffusion Models: Ordinary vs Stochastic Differential Equations Yu Cao · Jingrun Chen · Yixin Luo · Xiang ZHOU |
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Workshop
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Generalised Hyperbolic State-space Models for Inference in Dynamic Systems Yaman Kindap · Simon Godsill |
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Poster
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Thu 15:00 |
Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations Anudhyan Boral · Zhong Yi Wan · Leonardo Zepeda-Núñez · James Lottes · Qing Wang · Yi-Fan Chen · John Anderson · Fei Sha |
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Workshop
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Physics-Informed Transformer Networks Fabricio Dos Santos · Tara Akhound-Sadegh · Siamak Ravanbakhsh |
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Workshop
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Towards stable real-world equation discovery with assessing differentiating quality influence Mikhail Masliaev · Ilya Markov · Ilya Markov · Alexander Hvatov · Alexander Hvatov |
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Poster
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Wed 15:00 |
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations Grégoire Mialon · Quentin Garrido · Hannah Lawrence · Danyal Rehman · Yann LeCun · Bobak Kiani · Bobak Kiani |