Copertina

Ultra Fast PDE Solving via Physics Guided Few-step Diffusion

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Kong, Cindy Xiangrui, Wang, Yueqi, Zheng, Haoyang, Luo, Weijian, Lin, Guang
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Ultra-Fast Language Generation via Discrete Diffusion Divergence Instruct
di: Zheng, Haoyang, et al.
Pubblicazione: (2025)

BLADE: Bayesian Langevin Active Discovery with Replica Exchange for Identification of Complex Systems
di: Kong, Cindy Xiangrui, et al.
Pubblicazione: (2025)

Diff-Instruct with Diffused Reward: Towards Principled One-step Generator RL
di: Wu, Junyi, et al.
Pubblicazione: (2026)

Reduced-Basis Deep Operator Learning for Parametric PDEs with Independently Varying Boundary and Source Data
di: Wang, Yueqi, et al.
Pubblicazione: (2025)

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

Diff-Instruct++: Training One-step Text-to-image Generator Model to Align with Human Preferences
di: Luo, Weijian
Pubblicazione: (2024)

VideoPDE: Unified Generative PDE Solving via Video Inpainting Diffusion Models
di: Li, Edward, et al.
Pubblicazione: (2025)

Uni-Instruct: One-step Diffusion Model through Unified Diffusion Divergence Instruction
di: Wang, Yifei, et al.
Pubblicazione: (2025)

Muti-Fidelity Prediction and Uncertainty Quantification with Laplace Neural Operators for Parametric Partial Differential Equations
di: Zheng, Haoyang, et al.
Pubblicazione: (2025)

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

LES-SINDy: Laplace-Enhanced Sparse Identification of Nonlinear Dynamical Systems
di: Zheng, Haoyang, et al.
Pubblicazione: (2024)

David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training
di: Luo, Weijian, et al.
Pubblicazione: (2024)

FastDiSS: Few-step Match Many-step Diffusion Language Model on Sequence-to-Sequence Generation--Full Version
di: Nguyen-Cong, Dat, et al.
Pubblicazione: (2026)

Fine-Tuning Diffusion Models for Molecular Generation via Reinforcement Learning and Fast Sampling
di: Lin, Guang, et al.
Pubblicazione: (2026)

Exploring Non-Convex Discrete Energy Landscapes: An Efficient Langevin-Like Sampler with Replica Exchange
di: Zheng, Haoyang, et al.
Pubblicazione: (2025)

SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models
di: Xue, Shuchen, et al.
Pubblicazione: (2023)

Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics
di: Zheng, Haoyang, et al.
Pubblicazione: (2024)

DiffusionRollout: Uncertainty-Aware Rollout Planning in Long-Horizon PDE Solving
di: Yoo, Seungwoo, et al.
Pubblicazione: (2026)

OpInf-LLM: Parametric PDE Solving with LLMs via Operator Inference
di: Wang, Zhuoyuan, et al.
Pubblicazione: (2026)

Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo
di: Zheng, Haoyang, et al.
Pubblicazione: (2024)

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

Topology-aware Neural Flux Prediction Guided by Physics
di: Jiang, Haoyang, et al.
Pubblicazione: (2025)

Towards Generalizable PDE Dynamics Forecasting via Physics-Guided Invariant Learning
di: Li, Siyang, et al.
Pubblicazione: (2025)

dUltra: Ultra-Fast Diffusion Language Models via Reinforcement Learning
di: Chen, Shirui, et al.
Pubblicazione: (2025)

MetaColloc: Optimization-Free PDE Solving via Meta-Learned Basis Functions
di: Yang, Zichuan
Pubblicazione: (2026)

UPS: Efficiently Building Foundation Models for PDE Solving via Cross-Modal Adaptation
di: Shen, Junhong, et al.
Pubblicazione: (2024)

Accelerating PDE Surrogates via RL-Guided Mesh Optimization
di: Meng, Yang, et al.
Pubblicazione: (2026)

Single and Few-step Diffusion for Generative Speech Enhancement
di: Lay, Bunlong, et al.
Pubblicazione: (2023)

BEKAN: Boundary condition-guaranteed evolutionary Kolmogorov-Arnold networks with radial basis functions for solving PDE problems
di: Kim, Bongseok, et al.
Pubblicazione: (2025)

Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective
di: Wang, Weixin, et al.
Pubblicazione: (2025)

Pre-Generating Multi-Difficulty PDE Data for Few-Shot Neural PDE Solvers
di: Choudhary, Naman, et al.
Pubblicazione: (2025)

Neural-Schwarz Tiling for Geometry-Universal PDE Solving at Scale
di: Secchi, Paolo, et al.
Pubblicazione: (2026)

Discovering Physical Directions in Weight Space: Composing Neural PDE Experts
di: Wang, Pengkai, et al.
Pubblicazione: (2026)

Text2PDE: Latent Diffusion Models for Accessible Physics Simulation
di: Zhou, Anthony, et al.
Pubblicazione: (2024)

Masked Auto-Regressive Variational Acceleration: Fast Inference Makes Practical Reinforcement Learning
di: Gu, Yuxuan, et al.
Pubblicazione: (2025)

Multi-Operator Few-Shot Learning for Generalization Across PDE Families
di: Li, Yile, et al.
Pubblicazione: (2025)

Physics-Informed Inference Time Scaling for Solving High-Dimensional PDE via Defect Correction
di: Fan, Zexi, et al.
Pubblicazione: (2025)

Solving Prior Distribution Mismatch in Diffusion Models via Optimal Transport
di: Wang, Zhanpeng, et al.
Pubblicazione: (2024)

Mercury: Ultra-Fast Language Models Based on Diffusion
di: Labs, Inception, et al.
Pubblicazione: (2025)

SymPlex: A Structure-Aware Transformer for Symbolic PDE Solving
di: Park, Yesom, et al.
Pubblicazione: (2026)