Copertina

DOF: Accelerating High-order Differential Operators with Forward Propagation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Li, Ruichen, Wang, Chuwei, Ye, Haotian, He, Di, Wang, Liwei
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

Accelerating PDE Data Generation via Differential Operator Action in Solution Space
di: Dong, Huanshuo, et al.
Pubblicazione: (2024)

Rethinking the Expressive Power of GNNs via Graph Biconnectivity
di: Zhang, Bohang, et al.
Pubblicazione: (2023)

A&B BNN: Add&Bit-Operation-Only Hardware-Friendly Binary Neural Network
di: Ma, Ruichen, et al.
Pubblicazione: (2024)

Latent Neural Operator for Solving Forward and Inverse PDE Problems
di: Wang, Tian, et al.
Pubblicazione: (2024)

Forward Learning with Differential Privacy
di: Feng, Mingqian, et al.
Pubblicazione: (2025)

Differential Privacy in Two-Layer Networks: How DP-SGD Harms Fairness and Robustness
di: Xu, Ruichen, et al.
Pubblicazione: (2026)

A Hybrid Kernel-Free Boundary Integral Method with Operator Learning for Solving Parametric Partial Differential Equations In Complex Domains
di: Ling, Shuo, et al.
Pubblicazione: (2024)

A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
di: Li, Chengrui, et al.
Pubblicazione: (2024)

A Deep Neural Network Framework for Solving Forward and Inverse Problems in Delay Differential Equations
di: Wang, Housen, et al.
Pubblicazione: (2024)

Differentiable Neural-Integrated Meshfree Method for Forward and Inverse Modeling of Finite Strain Hyperelasticity
di: Du, Honghui, et al.
Pubblicazione: (2024)

EFKAN: A KAN-Integrated Neural Operator For Efficient Magnetotelluric Forward Modeling
di: Wang, Feng, et al.
Pubblicazione: (2025)

Moonwalk: Inverse-Forward Differentiation
di: Krylov, Dmitrii, et al.
Pubblicazione: (2024)

CHORDS: Diffusion Sampling Accelerator with Multi-core Hierarchical ODE Solvers
di: Han, Jiaqi, et al.
Pubblicazione: (2025)

Sampling in High-Dimensions using Stochastic Interpolants and Forward-Backward Stochastic Differential Equations
di: George, Anand Jerry, et al.
Pubblicazione: (2025)

Metric Learning to Accelerate Convergence of Operator Splitting Methods for Differentiable Parametric Programming
di: King, Ethan, et al.
Pubblicazione: (2024)

EM-GANSim: Real-time and Accurate EM Simulation Using Conditional GANs for 3D Indoor Scenes
di: Wang, Ruichen, et al.
Pubblicazione: (2024)

Deep Learning with Information Fusion and Model Interpretation for Health Monitoring of Fetus based on Long-term Prenatal Electronic Fetal Heart Rate Monitoring Data
di: Lin, Zenghui, et al.
Pubblicazione: (2024)

Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations
di: Behroozi, Abdolmehdi, et al.
Pubblicazione: (2025)

The Limits of Differential Privacy in Online Learning
di: Li, Bo, et al.
Pubblicazione: (2024)

Forward Target Propagation: A Forward-Only Approach to Global Error Credit Assignment via Local Losses
di: As-Saquib, Nazmus Saadat, et al.
Pubblicazione: (2025)

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
di: Cheng, Ze, et al.
Pubblicazione: (2025)

Second-Order Forward-Mode Automatic Differentiation for Optimization
di: Cobb, Adam D., et al.
Pubblicazione: (2024)

Training Large-Scale Optical Neural Networks with Two-Pass Forward Propagation
di: Ahmadnejad, Amirreza, et al.
Pubblicazione: (2024)

Component Fourier Neural Operator for Singularly Perturbed Differential Equations
di: Li, Ye, et al.
Pubblicazione: (2024)

Revisiting Pre-Propagation GNNs: Robust Diffusion Operators and Hidden-State Re-Propagation
di: Yue, Zichao, et al.
Pubblicazione: (2026)

Adaptive SGD with Line-Search and Polyak Stepsizes: Nonconvex Convergence and Accelerated Rates
di: Wu, Haotian
Pubblicazione: (2025)

Balancing the Reasoning Load: Difficulty-Differentiated Policy Optimization with Length Redistribution for Efficient and Robust Reinforcement Learning
di: Xia, Yinan, et al.
Pubblicazione: (2026)

$\widetilde{O}(N^2)$ Representation of General Continuous Anti-symmetric Function
di: Ye, Haotian, et al.
Pubblicazione: (2024)

Mono-Forward: Revisiting Forward-Forward through Objective-Locality Decomposition
di: Gong, James, et al.
Pubblicazione: (2025)

The Power of Active Multi-Task Learning in Reinforcement Learning from Human Feedback
di: Chen, Ruitao, et al.
Pubblicazione: (2024)

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

Recurrent Joint Embedding Predictive Architecture with Recurrent Forward Propagation Learning
di: Velarde, Osvaldo M, et al.
Pubblicazione: (2024)

An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization
di: Cao, Jincheng, et al.
Pubblicazione: (2024)

Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
di: Zhang, Bohang, et al.
Pubblicazione: (2024)

Breaking the Memory Wall: Exact Analytical Differentiation via Tiled Operator-Space Evolution
di: Wang, Shuhuan, et al.
Pubblicazione: (2025)

DNA: Differentiable Network-Accelerator Co-Search
di: Zhang, Yongan, et al.
Pubblicazione: (2020)

An update to PYRO-NN: A Python Library for Differentiable CT Operators
di: Schneider, Linda-Sophie, et al.
Pubblicazione: (2025)

Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems
di: Long, Da, et al.
Pubblicazione: (2024)

Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration
di: Han, Jiaqi, et al.
Pubblicazione: (2026)