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13 Results
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Poster
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Wed 11:00 |
Physics-Informed Variational State-Space Gaussian Processes Oliver Hamelijnck · Arno Solin · Theodoros Damoulas |
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Poster
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Fri 16:30 |
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees Alexander Terenin · David Burt · Artem Artemev · Seth Flaxman · Mark van der Wilk · Carl Edward Rasmussen · Hong Ge |
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Workshop
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Sun 8:30 |
Invited talk: data-driven vs inductive bias-driven methods in machine learning and the physical sciences Lukas Heinrich |
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Workshop
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FEABench: Evaluating Language Models on Real World Physics Reasoning Ability Nayantara Mudur · Hao Cui · Subhashini Venugopalan · Paul Raccuglia · Michael Brenner · Peter Norgaard |
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Workshop
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A Probabilistic Generative Method for Safe Physical System Control Problems Peiyan Hu · Xiaowei Qian · Wenhao Deng · Rui Wang · Haodong Feng · Ruiqi Feng · Tao Zhang · Long Wei · Yue Wang · Zhi-Ming Ma · Tailin Wu |
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Workshop
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Sun 9:00 |
Panel: data-driven vs inductive bias-driven methods in machine learning and the physical sciences Animashree Anandkumar · Naoya Takeishi · Johannes Brandstetter |
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Poster
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Thu 16:30 |
Mutual Information Estimation via Normalizing Flows Ivan Butakov · Aleksandr Tolmachev · Sofia Malanchuk · Anna Neopryatnaya · Alexey Frolov |
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Workshop
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The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning Ruben Ohana · Michael McCabe · Lucas Meyer · Rudy Morel · Fruzsina Agocs · Miguel Beneitez · Marsha Berger · Blakesly Burkhart · Stuart Dalziel · Drummond Fielding · Daniel Fortunato · Jared Goldberg · Keiya Hirashima · Yan-Fei Jiang · Rich Kerswell · Suryanarayana Maddu · Jonah Miller · Payel Mukhopadhyay · Stefan Nixon · Jeff Shen · Romain Watteaux · Bruno Régaldo-Saint Blancard · Liam Parker · Miles Cranmer · Shirley Ho |
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Competition
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Sat 13:50 |
#1st Place- MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability Fabien Casenave |
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Workshop
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Convergence Guarantees for Neural Network-Based Hamilton–Jacobi Reachability William Hofgard |
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Workshop
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Convolutional Hierarchical Deep Learning Neural Networks-Tensor Decomposition (C-HiDeNN-TD): a scalable surrogate modeling approach for large-scale physical systems Jiachen Guo · Chanwook Park · Xiaoyu Xie · Zhongsheng Sang · Gregory J. Wagner · Kam Liu |
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Poster
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Wed 16:30 |
Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations Artem Agafonov · Petr Ostroukhov · Roman Mozhaev · Konstantin Yakovlev · Eduard Gorbunov · Martin Takac · Alexander Gasnikov · Dmitry Kamzolov |