{"total":21,"rows":[{"id":"2505.17638","title":"Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training","created":"2025-05-23","cited_by_count":81,"area":"diffusion"},{"id":"2412.04833","title":"Wavelet Diffusion Neural Operator","created":"2024-12-06","cited_by_count":29,"area":"diffusion"},{"id":"2503.22600","title":"Generative Latent Neural PDE Solver using Flow Matching","created":"2025-03-28","cited_by_count":28,"area":"diffusion"},{"id":"2506.08604","title":"Physics vs Distributions: Pareto Optimal Flow Matching with Physics Constraints","created":"2025-06-10","cited_by_count":28,"area":"diffusion"},{"id":"2408.02965","title":"Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator","created":"2024-08-06","cited_by_count":12,"area":"diffusion"},{"id":"2404.08412","title":"PiRD: Physics-informed Residual Diffusion for Flow Field Reconstruction","created":"2024-04-12","cited_by_count":10,"area":"diffusion"},{"id":"2311.06112","title":"Turbulence Scaling from Deep Learning Diffusion Generative Models","created":"2023-11-10","cited_by_count":8,"area":"diffusion"},{"id":"2506.00214","title":"Diff-SPORT: Diffusion-based Sensor Placement Optimization and Reconstruction of Turbulent flows in urban environments","created":"2025-05-30","cited_by_count":8,"area":"diffusion"},{"id":"2407.00735","title":"Generative prediction of flow fields around an obstacle using the diffusion model","created":"2024-06-30","cited_by_count":6,"area":"diffusion"},{"id":"2410.23893","title":"DiffBatt: A Diffusion Model for Battery Degradation Prediction and Synthesis","created":"2024-10-31","cited_by_count":6,"area":"diffusion"},{"id":"2502.02205","title":"From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control","created":"2025-02-04","cited_by_count":3,"area":"diffusion"},{"id":"2605.03399","title":"PODiff: Latent Diffusion in Proper Orthogonal Decomposition Space for Scientific Super-Resolution","created":"2026-05-05","cited_by_count":2,"area":"diffusion"},{"id":"2606.11277","title":"Least-Action-Guided Diffusion for Physical Extrapolation","created":"2026-06-09","cited_by_count":2,"area":"diffusion"},{"id":"2410.23971","title":"Stochastic Reconstruction of Gappy Lagrangian Turbulent Signals by Conditional Diffusion Models","created":"2024-10-31","cited_by_count":1,"area":"diffusion"},{"id":"2606.06658","title":"Capturing non-Markovian dynamics in non-equilibrium stochastic systems using flow matching","created":"2026-06-04","cited_by_count":1,"area":"diffusion"},{"id":"2403.17993","title":"Mixing Artificial and Natural Intelligence: From Statistical Mechanics to AI and Back to Turbulence","created":"2024-03-26","cited_by_count":0,"area":"diffusion"},{"id":"2512.01572","title":"Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascade","created":"2025-12-01","cited_by_count":0,"area":"diffusion"},{"id":"2512.24813","title":"Learning Temporally Consistent Turbulence Between Sparse Snapshots via Diffusion Models","created":"2025-12-31","cited_by_count":0,"area":"diffusion"},{"id":"2603.06615","title":"Annealed Co-Generation: Disentangling Variables via Progressive Pairwise Modeling","created":"2026-02-20","cited_by_count":0,"area":"diffusion"},{"id":"2604.10074","title":"Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs","created":"2026-04-11","cited_by_count":0,"area":"diffusion"},{"id":"2610.16582","title":"Characterizing and Mitigating Distributional Bias in Physics-Informed Generative Models","created":"2026-10-12","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}