Cover Image

Accelerating PDE Surrogates via RL-Guided Mesh Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Meng, Yang, Jiang, Ruoxi, Zhao, Zhuokai, Liu, Chong, Willett, Rebecca, Chen, Yuxin
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Direct Acquisition Optimization for Low-Budget Active Learning
by: Zhao, Zhuokai, et al.
Published: (2024)

Embed and Emulate: Contrastive representations for simulation-based inference
by: Jiang, Ruoxi, et al.
Published: (2024)

Training neural operators to preserve invariant measures of chaotic attractors
by: Jiang, Ruoxi, et al.
Published: (2023)

Deep Stochastic Mechanics
by: Orlova, Elena, et al.
Published: (2023)

Hierarchical Implicit Neural Emulators
by: Jiang, Ruoxi, et al.
Published: (2025)

Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet
by: Adrian, Melissa, et al.
Published: (2024)

Accelerating Simulation of Two-Phase Flows with Neural PDE Surrogates
by: Poels, Yoeri, et al.
Published: (2024)

STO-RL: Offline RL under Sparse Rewards via LLM-Guided Subgoal Temporal Order
by: Gu, Chengyang, et al.
Published: (2026)

Adaptive Mesh-Quantization for Neural PDE Solvers
by: Dool, Winfried van den, et al.
Published: (2025)

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
by: Cheng, Ze, et al.
Published: (2025)

Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient?
by: Kim, Hwanwoo, et al.
Published: (2025)

Provable Accelerated Bayesian Optimization with Knowledge Transfer
by: Lin, Haitao, et al.
Published: (2025)

ReLU Neural Networks with Linear Layers are Biased Towards Single- and Multi-Index Models
by: Parkinson, Suzanna, et al.
Published: (2023)

Proposal-Guided Greedy Surrogate Refinement for PDE-Driven High-Dimensional Rare-Event Estimation
by: Gao, Zhiwei, et al.
Published: (2026)

Enhancing Vision-Language Model Reliability with Uncertainty-Guided Dropout Decoding
by: Fang, Yixiong, et al.
Published: (2024)

Predicting Change, Not States: An Alternate Framework for Neural PDE Surrogates
by: Zhou, Anthony, et al.
Published: (2024)

Accelerating PDE Data Generation via Differential Operator Action in Solution Space
by: Dong, Huanshuo, et al.
Published: (2024)

How do simple rotations affect the implicit bias of Adam?
by: DePavia, Adela, et al.
Published: (2025)

Constrained Multi-objective Bayesian Optimization through Optimistic Constraints Estimation
by: Li, Diantong, et al.
Published: (2024)

Surrogate Ensemble in Expensive Multi-Objective Optimization via Deep Q-Learning
by: Wu, Yuxin, et al.
Published: (2026)

SortedRL: Accelerating RL Training for LLMs through Online Length-Aware Scheduling
by: Zhang, Yiqi, et al.
Published: (2026)

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates
by: Huang, Yunfei, et al.
Published: (2025)

A Model-Guided Neural Network Method for the Inverse Scattering Problem
by: Tsang, Olivia, et al.
Published: (2025)

Integrating Uncertainty Awareness into Conformalized Quantile Regression
by: Rossellini, Raphael, et al.
Published: (2023)

Stabilizing black-box model selection with the inflated argmax
by: Adrian, Melissa, et al.
Published: (2024)

Learning from Less: SINDy Surrogates in RL
by: Dixit, Aniket, et al.
Published: (2025)

Moving Sampling Physics-informed Neural Networks induced by Moving Mesh PDE
by: Yang, Yu, et al.
Published: (2023)

MetaColloc: Optimization-Free PDE Solving via Meta-Learned Basis Functions
by: Yang, Zichuan
Published: (2026)

Preference Optimization with Multi-Sample Comparisons
by: Wang, Chaoqi, et al.
Published: (2024)

Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers
by: Chen, Chuqi, et al.
Published: (2024)

Structure-Aware Epistemic Uncertainty Quantification for Neural Operator PDE Surrogates
by: Song, Haoze, et al.
Published: (2026)

End-to-End Mesh Optimization of a Hybrid Deep Learning Black-Box PDE Solver
by: Ma, Shaocong, et al.
Published: (2024)

Accelerating Transformers in Online RL
by: Zelezetsky, Daniil, et al.
Published: (2025)

Towards Generalizable PDE Dynamics Forecasting via Physics-Guided Invariant Learning
by: Li, Siyang, et al.
Published: (2025)

RL-Selector: Reinforcement Learning-Guided Data Selection via Redundancy Assessment
by: Yang, Suorong, et al.
Published: (2025)

Gradient-Informed Temporal Sampling Improves Rollout Accuracy in PDE Surrogate Training
by: Wang, Wenshuo, et al.
Published: (2026)

GLOBE: Accurate and Generalizable PDE Surrogates using Domain-Inspired Architectures and Equivariances
by: Sharpe, Peter
Published: (2025)

Ultra Fast PDE Solving via Physics Guided Few-step Diffusion
by: Kong, Cindy Xiangrui, et al.
Published: (2026)

Deep Learning-Accelerated Surrogate Optimization for High-Dimensional Well Control in Stress-Sensitive Reservoirs
by: Valiyev, Mahammad, et al.
Published: (2026)

Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment
by: Wang, Chaoqi, et al.
Published: (2025)