Discovering and forecasting extreme events via active learning in neural operators

5 April 2022

Papers citing "Discovering and forecasting extreme events via active learning in neural operators"

21 / 21 papers shown

Title
LAPD: Langevin-Assisted Bayesian Active Learning for Physical Discovery Cindy Xiangrui Kong Haoyang Zheng Guang Lin AI4CE 42 0 0 04 Mar 2025
Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology Mario De Florio Zongren Zou Daniele E. Schiavazzi George Karniadakis 28 3 0 13 Aug 2024
Active Learning for Neural PDE Solvers Daniel Musekamp Marimuthu Kalimuthu David Holzmüller Makoto Takamoto Carlos Fernandez AI4CE 52 4 0 02 Aug 2024
Evaluating the Role of Data Enrichment Approaches Towards Rare Event Analysis in Manufacturing Chathurangi Shyalika Ruwan Wickramarachchi Fadi El Kalach R. Harik Amit Sheth 26 3 0 01 Jul 2024
Active search for Bifurcations Y. M. Psarellis T. Sapsis Ioannis G. Kevrekidis 31 0 0 17 Jun 2024
Leveraging viscous Hamilton-Jacobi PDEs for uncertainty quantification in scientific machine learning Zongren Zou Tingwei Meng Paula Chen Jérome Darbon George Karniadakis 52 7 0 12 Apr 2024
Stochastic Latent Transformer: Efficient Modelling of Stochastically Forced Zonal Jets Ira J. S. Shokar R. Kerswell Peter H. Haynes 24 3 0 25 Oct 2023
A generalized likelihood-weighted optimal sampling algorithm for rare-event probability quantification Xianliang Gong Yulin Pan 13 1 0 22 Oct 2023
Multi-Resolution Active Learning of Fourier Neural Operators Shibo Li Xin Yu Wei W. Xing Mike Kirby Akil Narayan Shandian Zhe AI4CE 25 4 0 29 Sep 2023
A Comprehensive Survey on Rare Event Prediction Chathurangi Shyalika Ruwan Wickramarachchi A. Sheth AI4TS 34 15 0 20 Sep 2023
A Data-Driven Approach to Morphogenesis under Structural Instability Yingjie Zhao Zhiping Xu AI4CE 9 2 0 23 Aug 2023
Evaluation of machine learning architectures on the quantification of epistemic and aleatoric uncertainties in complex dynamical systems Stephen Guth A. Mojahed T. Sapsis AI4CE 23 2 0 27 Jun 2023
Learning Functional Transduction Mathieu Chalvidal Thomas Serre Rufin VanRullen AI4CE 35 2 0 01 Feb 2023
Implementation of the Critical Wave Groups Method with Computational Fluid Dynamics and Neural Networks K. Silva K. Maki 13 3 0 24 Jan 2023
Improved generalization with deep neural operators for engineering systems: Path towards digital twin Kazuma Kobayashi James Daniell S. B. Alam AI4CE 33 20 0 17 Jan 2023
An adaptive multi-fidelity sampling framework for safety analysis of connected and automated vehicles Xianliang Gong Shuo Feng Yulin Pan 57 6 0 25 Oct 2022
Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models Ethan Pickering T. Sapsis 21 6 0 27 Aug 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 25 36 0 25 Aug 2022
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 211 2,287 0 18 Oct 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015