Cover Image

Enabling Automatic Differentiation with Mollified Graph Neural Operators

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lin, Ryan Y., Berner, Julius, Duruisseaux, Valentin, Pitt, David, Leibovici, Daniel, Kossaifi, Jean, Azizzadenesheli, Kamyar, Anandkumar, Anima
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning
by: Berner, Julius, et al.
Published: (2025)

Fourier Neural Operators Explained: A Practical Perspective
by: Duruisseaux, Valentin, et al.
Published: (2025)

A Library for Learning Neural Operators
by: Kossaifi, Jean, et al.
Published: (2024)

Neural Operators with Localized Integral and Differential Kernels
by: Liu-Schiaffini, Miguel, et al.
Published: (2024)

Neural Operators for Accelerating Scientific Simulations and Design
by: Azizzadenesheli, Kamyar, et al.
Published: (2023)

Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs
by: Rahman, Md Ashiqur, et al.
Published: (2024)

Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction
by: Ma, Ziqi, et al.
Published: (2024)

Fourier Neural Operators for Learning Dynamics in Quantum Spin Systems
by: Shah, Freya, et al.
Published: (2024)

Guaranteed Approximation Bounds for Mixed-Precision Neural Operators
by: Tu, Renbo, et al.
Published: (2023)

Equivariant Graph Neural Operator for Modeling 3D Dynamics
by: Xu, Minkai, et al.
Published: (2024)

Dynamical Measure Transport and Neural PDE Solvers for Sampling
by: Sun, Jingtong, et al.
Published: (2024)

FC-PINO: High Precision Physics-Informed Neural Operators via Fourier Continuation
by: Ganeshram, Adarsh, et al.
Published: (2022)

Solving Poisson Equations using Neural Walk-on-Spheres
by: Nam, Hong Chul, et al.
Published: (2024)

Guided Diffusion Sampling on Function Spaces with Applications to PDEs
by: Yao, Jiachen, et al.
Published: (2025)

TensorGRaD: Tensor Gradient Robust Decomposition for Memory-Efficient Neural Operator Training
by: Loeschcke, Sebastian, et al.
Published: (2025)

Neural Operator: Learning Maps Between Function Spaces
by: Kovachki, Nikola, et al.
Published: (2021)

Incremental Spatial and Spectral Learning of Neural Operators for Solving Large-Scale PDEs
by: George, Robert Joseph, et al.
Published: (2022)

NOBLE -- Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models
by: Ghafourpour, Luca, et al.
Published: (2025)

Scale-Consistent Learning for Partial Differential Equations
by: Li, Zongyi, et al.
Published: (2025)

Ultrasound Lung Aeration Map via Physics-Aware Neural Operators
by: Wang, Jiayun, et al.
Published: (2025)

Coarse Graining with Neural Operators for Simulating Chaotic Systems
by: Wang, Chuwei, et al.
Published: (2024)

Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds
by: O'Connell, Michael, et al.
Published: (2022)

Physics-Aware Neural Operators for Direct Inversion in 3D Photoacoustic Tomography
by: Wang, Jiayun, et al.
Published: (2025)

Decoupled Diffusion Sampling for Inverse Problems on Function Spaces
by: Lin, Thomas Y. L., et al.
Published: (2026)

Operator Learning Using Weak Supervision from Walk-on-Spheres
by: Viswanath, Hrishikesh, et al.
Published: (2026)

An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific Simulations
by: Duruisseaux, Valentin, et al.
Published: (2023)

Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
by: Ishfaq, Haque, et al.
Published: (2023)

Self-Supervised Learning via Flow-Guided Neural Operator on Time-Series Data
by: Nguyen, Duy, et al.
Published: (2026)

Mechanistic Interpretability with Sparse Autoencoder Neural Operators
by: Tolooshams, Bahareh, et al.
Published: (2025)

Physics-informed Neural-operator Predictive Control for Drag Reduction in Turbulent Flows
by: Zhao, Zelin, et al.
Published: (2025)

Neural Spline Operators for Risk Quantification in Stochastic Systems
by: Wang, Zhuoyuan, et al.
Published: (2025)

Sequential Controlled Langevin Diffusions
by: Chen, Junhua, et al.
Published: (2024)

Mesh-Informed Neural Operator : A Transformer Generative Approach
by: Shi, Yaozhong, et al.
Published: (2025)

Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
by: Li, Zongyi, et al.
Published: (2022)

Exploring the design space of deep-learning-based weather forecasting systems
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2024)

Universal Functional Regression with Neural Operator Flows
by: Shi, Yaozhong, et al.
Published: (2024)

Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing
by: Zhang, Bingliang, et al.
Published: (2024)

Ambient Noise Full Waveform Inversion with Neural Operators
by: Zou, Caifeng, et al.
Published: (2025)

DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training
by: Hao, Zhongkai, et al.
Published: (2024)

Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces
by: Liu-Schiaffini, Miguel, et al.
Published: (2023)