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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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Multimodal base distributions for continuous-time normalising flows
Shane Josias · Willie Brink
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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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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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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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Generalized One-Shot Transfer Learning of Linear Ordinary and Partial Differential Equations
Pavlos Protopapas · Hari Raval
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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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Physics-Informed Transformer Networks
Fabricio Dos Santos · Tara Akhound-Sadegh · Siamak Ravanbakhsh
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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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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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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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