{"total":21,"rows":[{"id":"2502.09692","title":"AB-UPT: Scaling Neural CFD Surrogates for High-Fidelity Automotive Aerodynamics Simulations via Anchored-Branched Universal Physics Transformers","created":"2025-02-13","cited_by_count":53,"area":null},{"id":"2411.16063","title":"VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics Prediction","created":"2024-11-25","cited_by_count":25,"area":null},{"id":"2601.01829","title":"RealPDEBench: A Benchmark for Complex Physical Systems with Real-World Data","created":"2026-01-05","cited_by_count":16,"area":null},{"id":"2502.06026","title":"A Multimodal PDE Foundation Model for Prediction and Scientific Text Descriptions","created":"2025-02-09","cited_by_count":10,"area":null},{"id":"2410.06366","title":"Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling","created":"2024-10-08","cited_by_count":9,"area":null},{"id":"2508.00643","title":"Light-Weight Diffusion Multiplier and Uncertainty Quantification for Fourier Neural Operators","created":"2025-08-01","cited_by_count":6,"area":null},{"id":"2505.20349","title":"FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation","created":"2025-05-25","cited_by_count":5,"area":null},{"id":"2509.20098","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","created":"2025-09-24","cited_by_count":3,"area":null},{"id":"2412.09752","title":"A Quasilinear Algorithm for Computing Higher-Order Derivatives of Deep Feed-Forward Neural Networks","created":"2024-12-12","cited_by_count":2,"area":null},{"id":"2501.13271","title":"Hybrid Two-Stage Reconstruction of Multiscale Subsurface Flow with Physics-informed Residual Connected Neural Operator","created":"2025-01-22","cited_by_count":2,"area":null},{"id":"2505.18857","title":"Hierarchical-embedding autoencoder with a predictor (HEAP) as efficient architecture for learning long-term evolution of complex multi-scale physical systems","created":"2025-05-24","cited_by_count":2,"area":null},{"id":"2509.10659","title":"M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations","created":"2025-09-12","cited_by_count":2,"area":null},{"id":"2606.24696","title":"A Physics-Informed Fourier-Wavelet Transformer for Multiscale Computational Fluid Dynamics Surrogate Modeling","created":"2026-06-23","cited_by_count":2,"area":null},{"id":"2509.06041","title":"Multi-Stage Graph Neural Networks for Data-Driven Prediction of Natural Convection in Enclosed Cavities","created":"2025-09-07","cited_by_count":1,"area":null},{"id":"2509.15900","title":"A Flow-rate-conserving CNN-based Domain Decomposition Method for Blood Flow Simulations","created":"2025-09-19","cited_by_count":1,"area":null},{"id":"2605.16966","title":"Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects","created":"2026-05-16","cited_by_count":1,"area":null},{"id":"2606.00296","title":"Is Zero-Shot Super-Resolution Possible in Operator Learning?","created":"2026-05-29","cited_by_count":1,"area":null},{"id":"2605.04198","title":"Deep Wave Network for Modeling Multi-Scale Physical Dynamics","created":"2026-05-05","cited_by_count":0,"area":null},{"id":"2608.29355","title":"APPSolver: Adaptive Patch Partitioning for Point-Wise Ship Flow Prediction on Unstructured Meshes","created":"2026-08-29","cited_by_count":0,"area":null},{"id":"2609.20857","title":"Reconstruction of 4D Mitral Regurgitation Hemodynamics from Sparse Planar Data using Deep Operator Networks with Test-Time Adaptation","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.34715","title":"PDE-JEPA: Predictive Representation Learning of Latent Dynamics Modeling for Parametric PDEs","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}