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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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Poster
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Tue 8:45
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A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization
Kansei Ushiyama · Shun Sato · Takayasu Matsuo
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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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Multimodal base distributions for continuous-time normalising flows
Shane Josias · Willie Brink
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Workshop
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Unifying Neural Controlled Differential Equations and Neural Flow for Irregular Time Series Classification
YongKyung Oh · Dongyoung Lim · SUNGIL KIM
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Workshop
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Manifold-augmented Eikonal Equations: Geodesic Distances and Flows on Differentiable Manifolds.
Daniel Kelshaw · Luca Magri
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Workshop
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CoNO: Complex Neural Operator for Continuous Dynamical Systems
Karn Tiwari · N M Anoop Krishnan · Prathosh AP
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Poster
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Thu 8:45
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Generalization bounds for neural ordinary differential equations and deep residual networks
Pierre Marion · Pierre Marion
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Workshop
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Data-Driven Neural-ODE Modeling for Breast Cancer Tumor Dynamics and Progression-Free Survival Predictions
Jinlin Xiang · Bozhao Qi · Qi Tang · Marc Cerou · Wei Zhao
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Workshop
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Causal Modeling with Stationary Diffusions
Lars Lorch · Andreas Krause · Bernhard Schölkopf
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Poster
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Thu 8:45
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Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models
Anant Raj · Umut Simsekli · Alessandro Rudi
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Workshop
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BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics
Suresh Bishnoi · Jayadeva Dr · Sayan Ranu · N M Anoop Krishnan
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