SOTAVerified

Operator learning

Learn an operator between infinite dimensional Hilbert spaces or Banach spaces

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 76–100 of 347 papers

TitleStatusHype
Operator Learning for Schrödinger Equation: Unitarity, Error Bounds, and Time GeneralizationCode0
Neural Functional: Learning Function to Scalar Maps for Neural PDE SurrogatesCode0
Multi-Level Monte Carlo Training of Neural Operators—0
Beyond Accuracy: EcoL2 Metric for Sustainable Neural PDE Solvers—0
Learning cardiac activation and repolarization times with operator learning—0
Physics-informed Multiple-Input Operators for efficient dynamic response prediction of structures—0
SetONet: A Deep Set-based Operator Network for Solving PDEs with permutation invariant variable input sampling—0
Data-driven operator learning for energy-efficient building control—0
A Hybrid Framework for Efficient Koopman Operator Learning—0
Geometry aware inference of steady state PDEs using Equivariant Neural Fields representationsCode0
Dimension reduction for derivative-informed operator learning: An analysis of approximation errors—0
Operator Learning: A Statistical Perspective—0
DeepOHeat-v1: Efficient Operator Learning for Fast and Trustworthy Thermal Simulation and Optimization in 3D-IC DesignCode0
Towards scientific machine learning for granular material simulations -- challenges and opportunities—0
Inverted Gaussian Process Optimization for Nonparametric Koopman Operator Discovery—0
New universal operator approximation theorem for encoder-decoder architectures (Preprint)—0
DeepOFormer: Deep Operator Learning with Domain-informed Features for Fatigue Life Prediction—0
EquiNO: A Physics-Informed Neural Operator for Multiscale SimulationsCode0
Invertible Koopman neural operator for data-driven modeling of partial differential equations—0
Data-Driven, ML-assisted Approaches to Problem Well-Posedness—0
Theory-to-Practice Gap for Neural Networks and Neural Operators—0
Physics-Informed Deep B-Spline Networks for Dynamical Systems—0
ON-Traffic: An Operator Learning Framework for Online Traffic Flow Estimation and Uncertainty Quantification from Lagrangian SensorsCode0
Active operator learning with predictive uncertainty quantification for partial differential equations—0
Cauchy Random Features for Operator Learning in Sobolev SpaceCode0
Show:102550
← PrevPage 4 of 14Next →

No leaderboard results yet.