Cover Image

Neural Control Variates with Automatic Integration

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Zilu, Yang, Guandao, Zhao, Qingqing, Deng, Xi, Guibas, Leonidas, Hariharan, Bharath, Wetzstein, Gordon
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Graphics Numerical Analysis
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Accurate Differential Operators for Hybrid Neural Fields
by: Chetan, Aditya, et al.
Published: (2023)

Diffusion Self-Distillation for Zero-Shot Customized Image Generation
by: Cai, Shengqu, et al.
Published: (2024)

Robust Symmetry Detection via Riemannian Langevin Dynamics
by: Je, Jihyeon, et al.
Published: (2024)

BlenderGym: Benchmarking Foundational Model Systems for Graphics Editing
by: Gu, Yunqi, et al.
Published: (2025)

PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers
by: Li, Songlin, et al.
Published: (2024)

A Neural-preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions
by: Lan, Kai Weixian, et al.
Published: (2023)

Self-Calibrating Gaussian Splatting for Large Field of View Reconstruction
by: Deng, Youming, et al.
Published: (2025)

Moving Sampling Physics-informed Neural Networks induced by Moving Mesh PDE
by: Yang, Yu, et al.
Published: (2023)

Energy-Controllable Time Integration for Elastodynamic Contact
by: You, Kevin, et al.
Published: (2026)

DiffusionPDE: Generative PDE-Solving Under Partial Observation
by: Huang, Jiahe, et al.
Published: (2024)

BlenderAlchemy: Editing 3D Graphics with Vision-Language Models
by: Huang, Ian, et al.
Published: (2024)

Autoregression-Free Neural Operators for Time-Dependent PDEs
by: Zhang, Jiaquan, et al.
Published: (2026)

Advancing the Understanding of Fixed Point Iterations in Deep Neural Networks: A Detailed Analytical Study
by: Ke, Yekun, et al.
Published: (2024)

Quasi-Framelets: Robust Graph Neural Networks via Adaptive Framelet Convolution
by: Yang, Mengxi, et al.
Published: (2022)

UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs
by: Han, Xi, et al.
Published: (2024)

PINNsur: Physics-Informed Neural Networks for PDEs on Curved Surfaces
by: Jain, Pranav, et al.
Published: (2026)

Geometric Integration for Neural Control Variates
by: Meister, Daniel, et al.
Published: (2025)

A Scientist Question: Research on the Impact of Super Structured Quadrilateral Meshes on Convergence and Accuracy of Finite Element Analysis
by: Zhao, Hui
Published: (2025)

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

Quasi-Random Physics-informed Neural Networks
by: Yu, Tianchi, et al.
Published: (2025)

CATO: Charted Attention for Neural PDE Operators
by: Cheng, Chun-Wun, et al.
Published: (2026)

Galerkin Method of Regularized Stokeslets for Procedural Fluid Flow with Control Curves
by: Sugimoto, Ryusuke, et al.
Published: (2024)

Monte Carlo-Type Neural Operator for Differential Equations
by: Choutri, Salah Eddine, et al.
Published: (2025)

Quantum Neural Network Restatement of Markov Jump Process
by: Zarezadeh, Z., et al.
Published: (2025)

A Dimensionality Reduction Approach for Convolutional Neural Networks
by: Meneghetti, Laura, et al.
Published: (2021)

Variational Geometry-aware Neural Network based Method for Solving High-dimensional Diffeomorphic Mapping Problems
by: Li, Zhiwen, et al.
Published: (2025)

Learning from Integral Losses in Physics Informed Neural Networks
by: Saleh, Ehsan, et al.
Published: (2023)

Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers
by: Zhou, Hang, et al.
Published: (2024)

Solving PDEs With Deep Neural Nets under General Boundary Conditions
by: Zhang, Chenggong
Published: (2025)

Better Neural PDE Solvers Through Data-Free Mesh Movers
by: Hu, Peiyan, et al.
Published: (2023)

Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling
by: Wang, Hong, et al.
Published: (2024)

Graph-Instructed Neural Networks for parametric problems with varying boundary conditions
by: Della Santa, Francesco, et al.
Published: (2026)

Training Stiff Neural Ordinary Differential Equations with Explicit Exponential Integration Methods
by: Fronk, Colby, et al.
Published: (2024)

Learning Semilinear Neural Operators : A Unified Recursive Framework For Prediction And Data Assimilation
by: Singh, Ashutosh, et al.
Published: (2024)

Beyond Loss Guidance: Using PDE Residuals as Spectral Attention in Diffusion Neural Operators
by: Sawhney, Medha, et al.
Published: (2025)

CFO: Learning Continuous-Time PDE Dynamics via Flow-Matched Neural Operators
by: Hou, Xianglong, et al.
Published: (2025)

Hierarchical Transformer Preconditioning for Interactive Physics Simulation
by: Osborne, Carl, et al.
Published: (2026)

Graph Neural Networks for Emulation of Finite-Element Ice Dynamics in Greenland and Antarctic Ice Sheets
by: Koo, Younghyun, et al.
Published: (2024)

Physics-Informed Neural Networks for High-Frequency and Multi-Scale Problems using Transfer Learning
by: Mustajab, Abdul Hannan, et al.
Published: (2024)

Graph Neural Network as Computationally Efficient Emulator of Ice-sheet and Sea-level System Model (ISSM)
by: Koo, Younghyun, et al.
Published: (2024)