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cs.LG2025
A Conformal Prediction Framework for Uncertainty Quantification in Physics-Informed Neural Networks
Yifan Yu, Cheuk Hin Ho, Yangshuai Wang
Physics-Informed Neural Networks (PINNs) have emerged as a powerful framework for solving PDEs, yet existing uncertainty quantification (UQ) approaches for PINNs generally lack rig…
math.OC2025
Accelerating a Linear Programming Algorithm on AMD GPUs
Xiyan Hu, Titus Parker, Connor Phillips +1
Linear Programming (LP) is a foundational optimization technique with widespread applications in finance, energy trading, and supply chain logistics. However, traditional Central P…
cs.AI2025
Collab-Solver: Collaborative Solving Policy Learning for Mixed-Integer Linear Programming
Siyuan Li, Yifan Yu, Zhihao Zhang +5
Mixed-integer linear programming (MILP) has been a fundamental problem in combinatorial optimization. Conventional MILP solving mainly relies on carefully designed heuristics embed…