2024 "neural operators" Papers
10 papers found
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
Levi Lingsch, Mike Yan Michelis, Emmanuel de Bézenac et al.
ICML 2024posterarXiv:2305.19663
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training
Zhongkai Hao, Chang Su, LIU SONGMING et al.
ICML 2024posterarXiv:2403.03542
Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws
Ning Liu, Yiming Fan, Xianyi Zeng et al.
ICML 2024spotlightarXiv:2312.11176
Improved Operator Learning by Orthogonal Attention
Zipeng Xiao, Zhongkai Hao, Bokai Lin et al.
ICML 2024spotlightarXiv:2310.12487
Neural operators meet conjugate gradients: The FCG-NO method for efficient PDE solving
Alexander Rudikov, Fanaskov Vladimir, Ekaterina Muravleva et al.
ICML 2024posterarXiv:2402.05598
Neural Operators with Localized Integral and Differential Kernels
Miguel Liu-Schiaffini, Julius Berner, Boris Bonev et al.
ICML 2024posterarXiv:2402.16845
Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning
Junfeng CHEN, Kailiang Wu
ICML 2024posterarXiv:2405.09285
Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations
Ze Cheng, Zhongkai Hao, Wang Xiaoqiang et al.
ICML 2024posterarXiv:2405.17509
Towards General Neural Surrogate Solvers with Specialized Neural Accelerators
Chenkai Mao, Robert Lupoiu, Tianxiang Dai et al.
ICML 2024posterarXiv:2405.02351
Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs
Chandra Mouli Sekar, Danielle Robinson, Shima Alizadeh et al.
ICML 2024poster