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Poster
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Thu 8:45
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D-CIPHER: Discovery of Closed-form Partial Differential Equations
Krzysztof Kacprzyk · Zhaozhi Qian · Mihaela van der Schaar
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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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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
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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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Sat 9:45
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Can Physics informed Neural Operators self improve?
Ritam Majumdar · Amey Varhade · Shirish Karande · Lovekesh Vig
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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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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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Wed 15:00
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Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
Grégoire Mialon · Quentin Garrido · Hannah Lawrence · Danyal Rehman · Yann LeCun · Bobak Kiani · Bobak Kiani
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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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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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Tue 15:15
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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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