Operator Learning for Reconstructing Flow Fields from Sparse Measurements: an Energy Transformer Approach

2 January 2025

Papers citing "Operator Learning for Reconstructing Flow Fields from Sparse Measurements: an Energy Transformer Approach"

7 / 7 papers shown

Title
Guided Diffusion Sampling on Function Spaces with Applications to PDEs Jiachen Yao Abbas Mammadov Julius Berner Gavin Kerrigan Jong Chul Ye Kamyar Azizzadenesheli A. Anandkumar DiffM 74 2 0 22 May 2025
Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method Conor Rowan K. Maute Alireza Doostan AI4CE 68 0 0 08 May 2025
Energy Transformer Benjamin Hoover Yuchen Liang Bao Pham Yikang Shen Hendrik Strobelt Duen Horng Chau Mohammed J Zaki Dmitry Krotov ViT 71 49 0 14 Feb 2023
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu Min Zhu Qinyan Tan Yadhu Kartha Lu Lu 86 377 0 21 Jul 2022
Physics-informed neural networks (PINNs) for fluid mechanics: A review Shengze Cai Zhiping Mao Zhicheng Wang Minglang Yin George Karniadakis PINN AI4CE 79 1,198 0 20 May 2021
Large Associative Memory Problem in Neurobiology and Machine Learning Dmitry Krotov J. Hopfield 58 142 0 16 Aug 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 248 2,150 0 08 Oct 2019