Cover Image

P3D: Scalable Neural Surrogates for High-Resolution 3D Physics Simulations with Global Context

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Holzschuh, Benjamin, Kohl, Georg, Redinger, Florian, Thuerey, Nils
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

PDE-Transformer: Efficient and Versatile Transformers for Physics Simulations
by: Holzschuh, Benjamin, et al.
Published: (2025)

Flow Matching for Posterior Inference with Simulator Feedback
by: Holzschuh, Benjamin, et al.
Published: (2024)

Tadpole: Autoencoders as Foundation Models for 3D PDEs with Online Learning
by: Liu, Qiang, et al.
Published: (2026)

Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation
by: Kohl, Georg, et al.
Published: (2023)

Uncertainty-aware Surrogate Models for Airfoil Flow Simulations with Denoising Diffusion Probabilistic Models
by: Liu, Qiang, et al.
Published: (2023)

Physics-based Deep Learning
by: Thuerey, N., et al.
Published: (2021)

The Unreasonable Effectiveness of Solving Inverse Problems with Neural Networks
by: Holl, Philipp, et al.
Published: (2024)

Differentiability in Unrolled Training of Neural Physics Simulators on Transient Dynamics
by: List, Bjoern, et al.
Published: (2024)

Neural Emulator Superiority: When Machine Learning for PDEs Surpasses its Training Data
by: Koehler, Felix, et al.
Published: (2025)

Learning to Estimate Single-View Volumetric Flow Motions without 3D Supervision
by: Franz, Aleksandra, et al.
Published: (2023)

ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks
by: Liu, Qiang, et al.
Published: (2024)

Stabilizing Backpropagation Through Time to Learn Complex Physics
by: Schnell, Patrick, et al.
Published: (2024)

PRDP: Progressively Refined Differentiable Physics
by: Bhatia, Kanishk, et al.
Published: (2025)

Light Transport-aware Diffusion Posterior Sampling for Single-View Reconstruction of 3D Volumes
by: Leonard, Ludwic, et al.
Published: (2025)

APEBench: A Benchmark for Autoregressive Neural Emulators of PDEs
by: Koehler, Felix, et al.
Published: (2024)

Symmetric Basis Convolutions for Learning Lagrangian Fluid Mechanics
by: Winchenbach, Rene, et al.
Published: (2024)

INC: An Indirect Neural Corrector for Auto-Regressive Hybrid PDE Solvers
by: Wei, Hao, et al.
Published: (2025)

PICT -- A Differentiable, GPU-Accelerated Multi-Block PISO Solver for Simulation-Coupled Learning Tasks in Fluid Dynamics
by: Franz, Aleksandra, et al.
Published: (2025)

CarBench: A Comprehensive Benchmark for Neural Surrogates on High-Fidelity 3D Car Aerodynamics
by: Elrefaie, Mohamed, et al.
Published: (2025)

Physics-embedded Fourier Neural Network for Partial Differential Equations
by: Xu, Qingsong, et al.
Published: (2024)

Optimization Landscapes Learned: Proxy Networks Boost Convergence in Physics-based Inverse Problems
by: Goyal, Girnar, et al.
Published: (2025)

Bias-Constrained Diffusion Schedules for PDE Emulations: Reconstruction Error Minimization and Efficient Unrolled Training
by: Cleï, Constantin Le, et al.
Published: (2026)

Component-Based Machine Learning for Indoor Flow and Temperature Fields Prediction Latent Feature Aggregation and Flow Interaction
by: Wang, Shaofan, et al.
Published: (2025)

3D Neural Operator-Based Flow Surrogates around 3D geometries: Signed Distance Functions and Derivative Constraints
by: Rabeh, Ali, et al.
Published: (2025)

5D Neural Surrogates for Nonlinear Gyrokinetic Simulations of Plasma Turbulence
by: Galletti, Gianluca, et al.
Published: (2025)

Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control
by: Becktepe, Jannis, et al.
Published: (2026)

Fourier Neural Operator Surrogate Model to Predict 3D Seismic Waves Propagation
by: Lehmann, Fanny, et al.
Published: (2023)

Physics vs Distributions: Pareto Optimal Flow Matching with Physics Constraints
by: Baldan, Giacomo, et al.
Published: (2025)

Stabilizing Test-Time Adaptation of High-Dimensional Simulation Surrogates via D-Optimal Statistics
by: Zimmel, Anna, et al.
Published: (2026)

CRAFT: Conflict-Resolved Aggregation for Federated Training
by: Wang, Ziqi, et al.
Published: (2026)

tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow
by: Xie, You, et al.
Published: (2018)

diffSPH: Differentiable Smoothed Particle Hydrodynamics for Adjoint Optimization and Machine Learning
by: Winchenbach, Rene, et al.
Published: (2025)

Anant-Net: Breaking the Curse of Dimensionality with Scalable and Interpretable Neural Surrogate for High-Dimensional PDEs
by: Menon, Sidharth S., et al.
Published: (2025)

Scalable Linearized Laplace Approximation via Surrogate Neural Kernel
by: Ortega, Luis A., et al.
Published: (2026)

Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling
by: Niu, Ruijia, et al.
Published: (2024)

Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication
by: Chen, Yunuo, et al.
Published: (2024)

Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models
by: Stotko, David, et al.
Published: (2023)

PMRT: A Training Recipe for Fast, 3D High-Resolution Aerodynamic Prediction
by: Jacob, Sam Jacob, et al.
Published: (2025)

Neural Network Surrogate Model for Junction Temperature and Hotspot Position in $3$D Multi-Layer High Bandwidth Memory (HBM) Chiplets under Varying Thermal Conditions
by: Zhang, Chengxin, et al.
Published: (2025)

Physics-Constrained Adaptive Flow Matching for Climate Downscaling
by: Debeire, Kevin, et al.
Published: (2026)