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Workshop
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Predicting the stabilization quantity with neural networks for Singularly Perturbed Partial Differential Equations
Sangeeta Yadav
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Poster
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Thu 13:30
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Random Grid Neural Processes for Parametric Partial Differential Equations
Arnaud Vadeboncoeur · Ieva Kazlauskaite · Yanni Papandreou · Fehmi Cirak · Mark Girolami · Omer Deniz Akyildiz
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Poster
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Thu 13:30
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Group Equivariant Fourier Neural Operators for Partial Differential Equations
Jacob Helwig · Xuan Zhang · Cong Fu · Jerry Kurtin · Stephan Wojtowytsch · Shuiwang Ji
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Poster
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Tue 14:00
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Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients
Marc Harkonen · Markus Lange-Hegermann · Bogdan Raita
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Workshop
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Infinite-Fidelity Surrogate Learning via High-order Gaussian Processes
Shibo Li · Li Shi · Shandian Zhe
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Oral
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Thu 18:56
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Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients
Marc Harkonen · Markus Lange-Hegermann · Bogdan Raita
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Poster
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Tue 14:00
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Predicting Ordinary Differential Equations with Transformers
Sören Becker · Michal Klein · Alexander Neitz · Giambattista Parascandolo · Niki Kilbertus
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Workshop
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On the Generalization Capacities of Neural Controlled Differential Equations
Linus Bleistein · Agathe Guilloux
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Poster
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Wed 17:00
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Controlled Differential Equations on Long Sequences via Non-standard Wavelets
Sourav Pal · Zhanpeng Zeng · Sathya Ravi · Vikas Singh
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Poster
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Wed 14:00
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Image Restoration with Mean-Reverting Stochastic Differential Equations
Ziwei Luo · Fredrik K. Gustafsson · Zheng Zhao · Jens Sjölund · Thomas Schön
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Workshop
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How to Select Physics-Informed Neural Networks in the Absence of Ground Truth: A Pareto Front-Based Strategy
Zhao Wei · Jian Cheng Wong · Nicholas Sung · Abhishek Gupta · Chin Chun Ooi · Pao-Hsiung Chiu · My Ha Dao · Yew Soon ONG
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Workshop
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Physics-Informed Neural Operator for Coupled Forward-Backward Partial Differential Equations
Xu Chen · Yongjie FU · Shuo Liu · Xuan Di
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