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Scaling Online Optimal Transport Minibatches for Flow Matching
Peter Chen, Sergey Levine
A central challenge in scaling flow models is maintaining stability in training and integration. In flow matching, this stability depends critically on how source samples are paire…
EUPHORIA: Efficient Universal Planning via Hybrid Optimization for Robust Industrial Robotic Assembly
Shih-Yu Lai, Chia-Ching Yen, Yang-Ting Shen +3
Robotic assembly in architectural construction faces a persistent bottleneck: existing planners are either highly specialized, requiring prohibitive retraining for every new geomet…
Displacement-Sparse Neural Optimal Transport
Peter Chen, Yue Xie, Qingpeng Zhang
Optimal transport (OT) aims to find a map that transports mass from one probability measure to another while minimizing a cost function. Recently, neural OT solvers have gained…
Learning Lagrangian Interaction Dynamics with Sampling-Based Model Order Reduction
Hrishikesh Viswanath, Yue Chang, Aleksey Panas +3
Simulating physical systems governed by Lagrangian dynamics often entails solving partial differential equations (PDEs) over high-resolution spatial domains, leading to significant…