{"total":65,"rows":[{"id":"2305.18035","title":"Physics-Informed Computer Vision: A Review and Perspectives","created":"2023-05-29","cited_by_count":28,"area":null},{"id":"2309.01909","title":"A Survey on Physics Informed Reinforcement Learning: Review and Open Problems","created":"2023-09-05","cited_by_count":24,"area":null},{"id":"2303.02063","title":"Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook","created":"2023-03-03","cited_by_count":11,"area":null},{"id":"2303.02304","title":"Coupled Multiwavelet Neural Operator Learning for Coupled Partial Differential Equations","created":"2023-03-04","cited_by_count":11,"area":null},{"id":"2308.02877","title":"Meta-learning in healthcare: A survey","created":"2023-08-05","cited_by_count":9,"area":null},{"id":"2403.15652","title":"Parametric Encoding with Attention and Convolution Mitigate Spectral Bias of Neural Partial Differential Equation Solvers","created":"2024-03-22","cited_by_count":9,"area":null},{"id":"2210.03426","title":"Certified machine learning: Rigorous a posteriori error bounds for PDE defined PINNs","created":"2022-10-07","cited_by_count":8,"area":null},{"id":"2403.15245","title":"Reasoning-Enhanced Object-Centric Learning for Videos","created":"2024-03-22","cited_by_count":7,"area":"lr"},{"id":"2509.03036","title":"Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models","created":"2025-09-03","cited_by_count":7,"area":null},{"id":"2308.02137","title":"Learning the solution operator of two-dimensional incompressible Navier-Stokes equations using physics-aware convolutional neural networks","created":"2023-08-04","cited_by_count":6,"area":null},{"id":"2209.15609","title":"$\\Phi$-DVAE: Physics-Informed Dynamical Variational Autoencoders for Unstructured Data Assimilation","created":"2022-09-30","cited_by_count":5,"area":null},{"id":"2408.01026","title":"PINNs for Medical Image Analysis: A Survey","created":"2024-08-02","cited_by_count":5,"area":null},{"id":"2506.10778","title":"SlotPi: Physics-informed Object-centric Reasoning Models","created":"2025-06-12","cited_by_count":5,"area":"lr"},{"id":"2508.20649","title":"Physics-Constrained Machine Learning for Chemical Engineering","created":"2025-08-28","cited_by_count":5,"area":null},{"id":"2407.05232","title":"PAPM: A Physics-aware Proxy Model for Process Systems","created":"2024-07-07","cited_by_count":4,"area":null},{"id":"2502.04131","title":"Structure is information: structural identifiability mappings for machine learning with partially observed dynamical systems","created":"2025-02-06","cited_by_count":4,"area":null},{"id":"2302.09446","title":"Estimating Treatment Effects in Continuous Time with Hidden Confounders","created":"2023-02-19","cited_by_count":3,"area":null},{"id":"2304.04664","title":"Inductive biases in deep learning models for weather prediction","created":"2023-04-06","cited_by_count":3,"area":null},{"id":"2508.19847","title":"Physics-Informed DeepONet Coupled with FEM for Convective Transport in Porous Media with Sharp Gaussian Sources","created":"2025-08-27","cited_by_count":3,"area":null},{"id":"2509.20098","title":"Incomplete Data, Complete Dynamics: A Diffusion Approach","created":"2025-09-24","cited_by_count":3,"area":null},{"id":"2305.14644","title":"KARNet: Kalman Filter Augmented Recurrent Neural Network for Learning World Models in Autonomous Driving Tasks","created":"2023-05-24","cited_by_count":2,"area":"wm"},{"id":"2401.11860","title":"A Review of Physics-Informed Machine Learning Methods with Applications to Condition Monitoring and Anomaly Detection","created":"2024-01-22","cited_by_count":2,"area":null},{"id":"2402.17664","title":"Bayesian Differentiable Physics for Cloth Digitalization","created":"2024-02-27","cited_by_count":2,"area":null},{"id":"2507.23018","title":"Data Readiness for Scientific AI at Scale","created":"2025-07-30","cited_by_count":2,"area":null},{"id":"2508.11528","title":"Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series","created":"2025-08-15","cited_by_count":2,"area":"diffusion"},{"id":"2511.15530","title":"Convergence and Sketching-Based Efficient Computation of Neural Tangent Kernel Weights in Physics-Based Loss","created":"2025-11-19","cited_by_count":2,"area":null},{"id":"2604.10125","title":"PhyMix: Towards Physically Consistent Single-Image 3D Indoor Scene Generation with Implicit--Explicit Optimization","created":"2026-04-11","cited_by_count":2,"area":null},{"id":"2605.25413","title":"Autoregression-Free Neural Operators for Time-Dependent PDEs","created":"2026-05-25","cited_by_count":2,"area":null},{"id":"2607.00196","title":"TRIE: An Evaluation Framework for Stochastic PDE Surrogates","created":"2026-06-30","cited_by_count":2,"area":null},{"id":"2310.01649","title":"On Training Derivative-Constrained Neural Networks","created":"2023-10-02","cited_by_count":1,"area":null},{"id":"2310.20463","title":"Interpretable Neural PDE Solvers using Symbolic Frameworks","created":"2023-10-31","cited_by_count":1,"area":null},{"id":"2402.14802","title":"Link Prediction with Physics-Inspired Graph Neural Networks","created":"2024-02-22","cited_by_count":1,"area":null},{"id":"2408.16599","title":"sEMG-Driven Physics-Informed Gated Recurrent Networks for Modeling Upper Limb Multi-Joint Movement Dynamics","created":"2024-08-29","cited_by_count":1,"area":null},{"id":"2504.09804","title":"BO-SA-PINNs: Self-adaptive physics-informed neural networks based on Bayesian optimization for automatically designing PDE solvers","created":"2025-04-14","cited_by_count":1,"area":null},{"id":"2506.09822","title":"Superstudent intelligence in thermodynamics","created":"2025-06-11","cited_by_count":1,"area":null},{"id":"2510.10483","title":"Gradient Enhanced Self-Training Physics-Informed Neural Network (gST-PINN) for Solving Nonlinear Partial Differential Equations","created":"2025-10-12","cited_by_count":1,"area":null},{"id":"2510.23149","title":"Complexity Dependent Error Rates for Physics-informed Statistical Learning via the Small-ball Method","created":"2025-10-27","cited_by_count":1,"area":null},{"id":"2512.06031","title":"Multi-resolution Physics-Aware Recurrent Convolutional Neural Network for Complex Flows","created":"2025-12-04","cited_by_count":1,"area":null},{"id":"2601.14810","title":"Learning and extrapolating scale-invariant processes","created":"2026-01-21","cited_by_count":1,"area":null},{"id":"2602.15704","title":"Controlled oscillation modeling using port-Hamiltonian neural networks","created":"2026-02-17","cited_by_count":1,"area":null},{"id":"2308.13222","title":"Bayesian Reasoning for Physics Informed Neural Networks","created":"2023-08-25","cited_by_count":0,"area":null},{"id":"2402.09018","title":"Neural Operators Meet Energy-based Theory: Operator Learning for Hamiltonian and Dissipative PDEs","created":"2024-02-14","cited_by_count":0,"area":null},{"id":"2407.11057","title":"SPIN: SE(3)-Invariant Physics Informed Network for Binding Affinity Prediction","created":"2024-07-10","cited_by_count":0,"area":null},{"id":"2503.05201","title":"Deep Muscle EMG construction using A Physics-Integrated Deep Learning approach","created":"2025-03-07","cited_by_count":0,"area":null},{"id":"2503.09113","title":"Constraint-Guided Learning of Data-driven Health Indicator Models: An Application on the Pronostia Bearing Dataset","created":"2025-03-12","cited_by_count":0,"area":null},{"id":"2505.12360","title":"LaPON: A Lagrange's-mean-value-theorem-inspired operator network for solving PDEs and its application on NSE","created":"2025-05-18","cited_by_count":0,"area":null},{"id":"2506.06308","title":"Scientific machine learning in Hydrology: a unified perspective","created":"2025-05-24","cited_by_count":0,"area":null},{"id":"2507.03183","title":"Knowledge-Guided Machine Learning: Illustrating the use of Explainable Boosting Machines to Identify Overshooting Tops in Satellite Imagery","created":"2025-07-02","cited_by_count":0,"area":null},{"id":"2508.07536","title":"Physics-Informed Multimodal Bearing Fault Classification under Variable Operating Conditions using Transfer Learning","created":"2025-08-11","cited_by_count":0,"area":null},{"id":"2509.05799","title":"Hybrid Fourier Neural Operator-Plasma Fluid Model for Fast and Accurate Multiscale Simulations of High Power Microwave Breakdown","created":"2025-09-06","cited_by_count":0,"area":null},{"id":"2510.03416","title":"Training Variation of Physically-Informed Deep Learning Models","created":"2025-10-03","cited_by_count":0,"area":null},{"id":"2510.26586","title":"Physics-Informed Mixture Models and Surrogate Models for Precision Additive Manufacturing","created":"2025-10-30","cited_by_count":0,"area":null},{"id":"2511.23256","title":"Robust HRRP Recognition under Interrupted Sampling Repeater Jamming using a Prior Jamming Information-Guided Network","created":"2025-11-28","cited_by_count":0,"area":null},{"id":"2512.02920","title":"Learning Multimodal Embeddings for Traffic Accident Prediction and Causal Estimation","created":"2025-12-02","cited_by_count":0,"area":null},{"id":"2512.09576","title":"Seeing Soil from Space: Towards Robust and Scalable Remote Soil Nutrient Analysis","created":"2025-12-10","cited_by_count":0,"area":null},{"id":"2512.13217","title":"Rethinking Physics-Informed Regression Beyond Training Loops and Bespoke Architectures","created":"2025-12-15","cited_by_count":0,"area":null},{"id":"2603.22380","title":"Symbolic Graph Networks for Robust PDE Discovery from Noisy Sparse Data","created":"2026-03-23","cited_by_count":0,"area":null},{"id":"2604.00256","title":"Informed Machine Learning with Knowledge Landmarks","created":"2026-03-31","cited_by_count":0,"area":null},{"id":"2604.27638","title":"Green Physics-Informed Machine Learning Models For Structural Health Monitoring","created":"2026-04-30","cited_by_count":0,"area":null},{"id":"2606.19378","title":"A Hybrid GNN-FEM Framework for Phase-Field Fracture Simulation. Physics-Preserving Hybridization for Generalizable Surrogate Modeling","created":"2026-06-12","cited_by_count":0,"area":null},{"id":"2608.02135","title":"Cardiovascular Digital Twins from Physics Based to Data Driven Approaches","created":"2026-08-03","cited_by_count":0,"area":null},{"id":"2608.14570","title":"Coarse-to-Fine Multi-Resolution Diffusion Models for Trajectory Generation in Urban Systems","created":"2026-06-05","cited_by_count":0,"area":"diffusion"},{"id":"2608.16873","title":"A Data-Efficient Analytical Prior Machine Learning Framework for Sound Reduction Frequency Prediction in Helmholtz Resonators","created":"2026-08-17","cited_by_count":0,"area":null},{"id":"2609.33387","title":"From Grey-Box to Green-Box: When can Physics-Informed Machine Learning Reduce Carbon Footprints in Structural Health Monitoring?","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2610.16504","title":"pi-Net: Empirical Latent Representations for Differentiable Physics Heads in Data-Scarce Systems","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}