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Datasets & Benchmarks (43)
Training & evaluation datasets, scientific ML benchmarks
- PDE-OBS Partial Differential Equation Benchmark Dataset
- Adaption Materials Science QA Augmented Dataset
- PDE Surrogate Benchmark Dataset
- OJOx: Specification-Conditioned Demonstrations for Embodied AI in Construction
- Science Materials Dataset
- SPUS PDE-UNet-36M Navier-Stokes PWC Model
- ColdPlate-CFD-2000sims: Liquid-Cooled Dual-Chip Pin-Fin Cold Plate CFD Dataset
- interpolant_pdes Dataset
- PDECert Natural-Candidate Pilot Benchmark
- Cross-Representation PDE Evaluation Dataset
- PDE Solver Code Perturbation Evaluation Dataset
- PDEControl_DPC - TI-DeepONet Training Datasets
- cluster-03-potential-flow-pinn Model
- Materials Platform for Data Science
- Downstream_Physics_Simulation Dataset
- Morocco Ait Melloul Station Daily Average Discharge Dataset 1970-2024
- CFD Surrogate Data
- CFDBench
- FuXi-CFD Dataset
- PDEBench
- TU Delft Turbulent Wake Dataset
- U-bend Thermal-Fluid Dataset
- CFD Benchmark Dataset
- CFDBench: Computational Fluid Dynamics Benchmark Dataset
- CFD Surrogate Data
- FuXi-CFD Wind Field Dataset
- 32wind-CFD Dataset
- PES2O Materials Science Pretraining Corpus 780M
- MaCroScope Physics 20k Cleaned Dataset
- PLAID
- MaCroScope-Physics-10k Physical Macroscopic Dataset
- MaCroScope-Physics-5k Dataset
- MaCroScope-Physics-1k Dataset
- MaCroScope-Physics-4k Dataset
- TIDE
- GeoPT Downstream Physics Simulation Dataset
- DrivAerNet++
- Materials Science and Engineering Domain Ontologies
- PDEArena
- The Well
- AirfRANS
- LeRobot Arm Test Dataset
- Materials Sciences Demo Dataset
Tools & Frameworks (38)
Solvers, training frameworks, post-processing & visualization tools
- InternS1-Mini Context-Conditioned Molecule Transfer Model
- Context-Conditioned Molecule Transfer Model for Carcinogens
- NTBuilder: Commensurate Construction of Nanotubes from Arbitrary Two-Dimensional Crystals and a Catalog of 20 Million Structures
- Warp-Geo: Differentiable Geometry Representation for Dynamic-Boundary Simulation and Shape Optimization
- NVIDIA Earth-2: AI-Powered Weather Decision Platform
- Unitree UnifoLM-WLA-1.0 General-Purpose Humanoid Robot Foundation Model
- SPUS-PDE-UNet-36M Navier-Stokes Supervised Learning Model
- PINN Heat Equation Solver
- TensorRT Edge-LLM Completes MLPerf Edge Agentic Benchmark 6.4x Faster on Jetson AGX Thor
- SPUS-PDE-UNet-36M: Neural PDE Solver with 36M Parameters
- PhysicsNeMo v2.2.2
- OneScience-Group/PINN-TC
- cluster-07-fourier-pinn
- cluster-06-bubble-dynamics-pinn
- cluster-02-hydrostatic-pinn
- Compressible Euler Equations PINN Model
- Physics-informed Neural Network CFD
- ai4collaboration/Qwen3-8B-Mixed-Biology-and-Physics-20K-GRPO
- Spherical Fourier Neural Operators
- FEniCS / FFCx
- Modin
- JAX-Fluids
- PETSc
- PyVista
- PhysicsNeMo
- FEniCS/dolfinx v0.11.0.post0 Released
- DeepXDE
- NeuralOperator
- Neural Operator Predictors for Sampled Measurements
- Fundamental Physics Neural Operators
- POSEIDON
- OpenFOAM
- SU2
- JAX-CFD
- DeepXDE v1.15.0
- CIFGS/physics-informed-sirenMRI-model
- NeuralOperator v2.0.0 Release
- DMD-Neural-Operator
Applied Cases (16)
Physics AI deployment cases in any domain - CAE, energy, weather, biomedicine, materials, geophysics and beyond
- NVIDIA Earth-2 Industrial Climate Prediction Platform
- Physics-Informed CNN for Battery Pack Temperature Fields
- HydroGym: A Reinforcement Learning Platform for Flow Control
- MACE-MP-0: A Universal Machine-Learned Interatomic Potential
- TopoDiff: Diffusion-Model-Driven Topology Optimization
- How to Use AI Agents to Prepare 3D Scenes for Simulation
- How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin
- Airfoil Aerodynamic Design & CFD Surrogate
- Vehicle External-Flow Surrogate & Wind-Tunnel Digitalization
- Long-Span Bridge Structural Health Monitoring & Digital Twin
- Wind-Turbine Blade Load Prediction & Surrogate
- Patient-Specific Hemodynamics via Hybrid Physics-Neural Surrogates
- GNoME: Graph Networks for Materials Exploration
- OpenFWI: Seismic Full Waveform Inversion
- GraphCast: Data-Driven Weather Forecasting
- Tokamak Plasma Magnetic Confinement Control
Learning Paths (17)
Resources from beginner to industrial deployment
- How to Use NVIDIA Warp and MjWarp to Accelerate Robotics Simulation and Learning Workflows
- Adaptive Physics-informed Neural Networks: A Survey
- Embedding Physics Priors in Robot Learning: A Survey
- Accelerating a ROS 2 Node with an AI Agent and NVIDIA Isaac ROS
- Neural Operator: Is data all you need to model the world? An insight into the paradigm of data-driven scientific ML
- From Theory to Application: A Practical Introduction to Neural Operators in Scientific Computing
- Machine Learning with Physics Knowledge for Prediction: A Survey
- Continuous-Time Machine Learning: A Unified Mathematical Perspective
- FNO (Fourier Neural Operator) Tutorial
- Finite Element from Scratch in Python
- DeepONet Getting Started
- Physics Simulation & ML Integration Roadmap
- Engineering Hybrid Physics-Informed Neural Networks for Next-Generation Electricity Systems: A State-of-the-Art Review
- Operator Learning: A Survey
- Physics-Based Deep Learning (Online Book)
- PINN from Scratch
- Lecture Notes on Physics Informed Neural Networks, Neural Operators, and Their Applications
Papers & Surveys (220)
Must-read benchmark papers and technical surveys (no news or industry reports)
- CFD Correction of Open Tip Clearance Flow in a Compressor Cascade Using VAE Latent Space Adaptation
- Leakage-Safe Machine Learning for Hydrogen Embrittlement Detection in 316L Stainless Steel: A Region-Held-Out Evaluation of Texture and Deep Features in SEM Micrographs
- Parnassus for the CLD Detector: A Generative Machine-Learning Surrogate for Detector Simulation and Reconstruction at the FCC-ee
- Deep-Learning Solvers and Surrogates for Infinity and p-Laplace Problems
- POPT: Physics-Informed Deep Learning for Phase-Only Positioning in Distributed MIMO
- Decision-Gated Surrogate-Assisted Stochastic Optimization with Independent High-Fidelity Certification for Photovoltaic Hosting-Capacity Planning
- Equation Discovery with Bayesian Tree-Adjoining Grammars
- Coupled Meta-Adaptive Filtering for Active Noise Control Under Time-Varying Acoustic Paths
- On the Limits of Univariate Deep Learning for Significant Wave Height Forecasting
- Architecture Acceleration of Machine Learning Gravitational Waveform Surrogate Models
- Gradient Surgery for Physics-Informed Neural Networks
- Conformal Symplectic Structure of Brinkman Penalisation for Structure-Preserving Operator Learning of Hamiltonian PDEs
- DNNsolver: Accurate and Efficient Deep Learning Modeling of Polarization-Sensitive Diffractive Neural Networks
- GridSFM: A Foundation Model for Solving AC Optimal Power Flow
- Towards Modeling the Hemodynamic Impact of Mitral and Aortic Valve Repair in Patients with Left Ventricular Assist Devices
- LeafNet: A Diffusion-Free Multi-Layer Neural Network Method for Multidimensional Nonlinear Hyperbolic Equations
- PR-Smoother: Simulator-Preserving Non-Gaussian Smoothing for Data Assimilation
- RFlash: Shadow Reduction in Ultrasound Imaging Using Differentiable Simulation and Radiance Field Decomposition
- Response-state Learning for Transferable Vibrational Spectroscopic Characterization with Electron Prior
- SHRAV: State-Hypothesis-Reason-Action-Verify Framework for Physical Modeling and Inverse Design
- TM4FF: Physics-Constrained Transformer-Mamba Framework for Flow Field Prediction
- Concentration of Stationary Measures onto Large Scales in the Fast-Advection Limit of the Stochastically Forced Two-Dimensional Navier-Stokes Equations
- Prediction of Re-Ignition Times in Dielectric Barrier Discharges
- GCN-Based Model for Fault Classification in Distribution Networks under Harmonic Distortion
- Simulation-Based Inference and Unbinned Asimov Construction with Hybrid Neural Density Estimation
- Physics-guided Inverse Design of Co-based Superalloys Using Machine Learning and Multi-objective Optimization for Enhanced γ' Solvus Temperature
- A Physics-Driven Framework for Parametric Periodic-Flow Modeling and Finite-Amplitude Aeroelastic Response Analysis
- Learning Operators of Geometry with an Interface Autoencoder
- Optimal Bias Potentials via Ergodic Optimal Control and Generator Learning
- Active Self-Consistent Field Theory for Ornstein-Uhlenbeck Polymers
- Elucidating the Conformal Structure of the Brinkman Penalisation Method for Geometry-Adapted, Structure-Preserving Operator Learning of Hamiltonian PDEs
- Data-Assimilation-Assisted Reinforcement Learning for Power Grid Control under Load Uncertainty
- A Harmonic-Regression ARMA Model for Rotating Machinery Dynamics Identification and Fault Detection Under Varying Conditions
- Temporal Interfaces in Metamaterials with Shape-Varying Inclusions
- Exact Equivariance from Ordinary Neural Networks for Lattice Many-Body Dynamics
- Relative periodic orbits in spatially extended Kolmogorov turbulence: from global to localized recurrence
- Combining physical models with dynamically acquired experimental information for the optimization of multicomponent NASICON fast ionic conductors in a self-driving laboratory
- Brain-to-Language Decoding: Tasks, Signals, Methods, Evaluation, Practical Use and Beyond
- Rational Design of Low-Dimensional Hybrid Organic/Inorganic Interfaces for Enhanced Second-Harmonic Generation
- Towards Extended Active Learning for Modelling Ferroelectric Switching: the Need for 'Gold Standards'
- FREESIA: Covariance-Aware Posterior Transport for Expressive and Scalable Data Assimilation
- CFD-Machine Learning Driven Pod Optimization and Staged Pressure-Area Management for Supersonic Evacuated Tube Transport
- Federating Quantum and Classical Computing: A Privacy-Preserving Hybrid Approach
- High-Order Variable-Scaled Energetic Variational Neural Networks for Phase-Field Gradient Flows
- An Unconditionally Stable Second-Order Robin Partitioned Method for Fluid-Poroelastic Structure Interaction
- Fast Surrogate for the Earth Matter Effect on Solar Neutrinos
- Finite-state automata for exact matrix product operators of tight-binding Hamiltonians: fractals, quasicrystals, trees and hyperbolic lattices
- Probabilistic Physics-Informed Neural Solvers for Woods-Saxon Parameter Identification
- MIISO: Modal Integrators for Isogeometric Stabilization of Outliers
- DNNsolver: Accurate and Efficient Deep Learning Modeling of Polarization-Sensitive Diffractive Neural Networks
- The Mechanics of Delta Learning: Target Design for Generalizable Scientific Machine Learning
- GINIO: A Geometric SO(3)-Equivariant Interface for Neural Inertial Odometry
- DissipNet: Data-driven Discrete-time Deep RNN-based Modeling for Dissipative Systems
- HOTICE: Whole-Body Humanoid Object Transportation in Cluttered Environments
- JAMB: Joint Action-Motion Diffusion for Bimanual Manipulation
- KATOsuper: Surrogate-accelerated neural topology optimization with sensitivity-consistent Fourier neural operators
- MENO: Memory-Efficient Neural Operator
- Physical-Layer Sensing Privacy via Constellation Shaping for OFDM-ISAC Systems: Theory, Design, and Experiments
- PISCES: Physics-Informed Solar-wind Convolutional AutoEncoder for Space-weather Anomaly Detection and Early Warning
- Transformer-Informed Trajectory Optimization for Relative Motion in Cislunar Orbits
- Convergence of the Original BGN Method for Mean Curvature Flow
- Runge-Kutta-Aligned Oscillation Elimination: Restoring Superconvergence for Fully Discrete Shock-Capturing DG Schemes
- AKAPINN: Adaptive Kolmogorov-Arnold Physics-Informed Neural Networks for approximating solutions to quasilinear partial differential equations
- Coupled Maxwell-Cable Framework for Action Potential Propagation in Branched Squid Giant Axons
- The Scott-Vogelius Element is Inf-Sup Stable on Freudenthal Meshes for k ≥ 4
- Predictive Uncertainty for Neural CAE Surrogates
- MARC-TS: Learning Continuous Reaction Paths for Transition-State Prediction
- Anisotropic Kernel-based Multilevel Interpolation of High-Dimensional Functions on Sparse Grids
- In-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization
- Impact of Chemical Clustering on the Structural, Topological, and Functional Properties of Ba(Zr_xTi_{1-x})O_3: An Atomistic Simulation Study
- Towards Adaptive Interaction Strategies for Human Companion Robot via Deep Reinforcement Learning
- Physics-guided inverse design of Co-based superalloys using machine learning and multi-objective optimization for enhanced gamma-prime solvus temperature
- Sparse-Observation Atmospheric Thermal Forecasting with Physics-Informed Neural Networks for Climate-Aware Digital Twins
- Meta-Optics-Based Diffractive Learning Machine for Angle-Multiplexed Multi-Task Processing
- Cosserat Modeling of Trimmed Helicoid Soft Arms with a Separated-Section Constitutive Law
- Doubly exponential convergence of the cyclic steepest descent method for strictly convex quadratics in arbitrary dimensions
- Physics-Informed Self-Supervised Learning for Joint Wire Calibration and Interaction Position Reconstruction in Multi-Wire Parallel Plate Avalanche Counters
- A Fully Implicit Electromagnetic Energy- and Charge-Conserving PIC Model for High-β Plasma Simulations
- Adaptive Physics Transformer with Fused Global-Local Attention for Subsurface Energy Systems
- ATOM: A Pretrained Neural Operator for Multitask Molecular Dynamics
- Transolver is a Linear Transformer: Revisiting Physics-Attention through the Lens of Linear Attention
- Uni-Macro-FRPN: Full-Resolution and Cross-Scale Learning for Polymers
- Two-Stage Ordering Kinetics in Binary Mixtures of Ellipsoidal Particles
- LPINNs: First-Layer Gated Localization for Physics-Informed Neural Networks
- Data-Driven MPC with Adaptively Sampled Non-Expert Demonstrations: Performance Guarantees and Sample Complexity
- Artificial Neural Networks as Surrogate Models in Black Box Optimization
- Combinatorial Optimization Augmented Machine Learning for Dynamic Electric Autonomous Dial-a-Ride Problem
- Adaptive Minimum-Variance Phase Gradient Estimator Overcomes Trainability Barriers in Neural-Network-Based Variational Quantum Optimization
- Domain-decomposed Evolutional Deep Neural Network with Random Features for Transient Pressure Diffusion with Discontinuous and High-Contrast Coefficients
- Conformal Spherical Splines for the Laplace-Beltrami Operator on Genus-Zero Surfaces
- Comparative Analysis of State-of-the-Art Foundation Models for Sleep Analysis Under Channel Reduction
- Scalable Incremental Robustness Analysis of Neural Network Feedback Systems
- Predicting Energy and Structural Response to Force Correction in Molecular Dynamics
- A Hybrid Quantum Neural Network to Analyse Big Experimental Powder X-ray Diffraction Data
- AffordanceWAM: Affordance-Aware Joint World-Action Modeling for Robot Manipulation
- Diff-NekRS: A Scalable Differentiable Framework for Multi-Timestep Solver-in-the-Loop Training
- AKAPINN: Adaptive Kolmogorov-Arnold Physics-Informed Neural Networks for Approximating Solutions to Quasilinear Partial Differential Equations
- CFD-Machine Learning Driven Pod Optimization and Staged Pressure-Area Management for Supersonic Evacuated Tube Transport
- DeepFEAv2: Deep Learning for Transient Finite Element Analysis Beyond Structured Meshes
- FAST-ML: A Hybrid Physics-Machine Learning Framework for Tropical Cyclone Intensity Forecasting
- When Does Test-Time Physical Diagnosis Pay? A Frozen Policy Buys Evidence It Never Reads
- Acoustic Dip in the Effective Temperature of Hot Brownian Motion
- TASE-Stabilized Time-Evolving Natural Gradient Methods for Diffusion-Dominated PDEs
- Cognitive behavior emerging in mechanical systems through reservoir encoding and active inference
- Bayesian Filtering in Physical Systems via Test-time Trained Flow Matching
- Exact Molecular Hessians from Local MLIPs in O(N) Time Using Sparse Differentiation
- Asymptotic preservation of an exponential Euler method under Hamiltonian fast advection with multiple critical points
- NeSTR: Neural S-Transform Reconstruction for Gaussian SPDEs
- NTBuilder: Commensurate Construction of Nanotubes from Arbitrary Two-Dimensional Crystals and a Catalog of 20 Million Structures
- D3DWA: Adaptive Weight and Prediction-Horizon for Dynamic Window Approach via Dueling Double Deep Q-Network
- Real-Time SiPM Pulse Deconvolution for a High-Granularity Dual-readout Calorimeter with Neural Networks
- DeViGrasp: Robust Visual Mobile Grasping for Quadruped Manipulators under Degraded Perception
- A subcell-refined entropy-residual-driven limiting strategy for high-order discontinuous Galerkin methods
- LiNiO2/NiO Phase Prediction Using Artificial Neural Networks
- CHOREO: Every Humanoid Skill as a Trajectory
- Equivariant Neural Prediction of the Stokes Resistance Tensors for Arbitrary Microparticle Shapes
- Receiver-Side Physics-Informed Residual Digital Twin for Predictive Fine Tracking in Inter-Satellite Optical Links
- Analysis of trade-offs in urban heat mitigation using a Bayesian Optimization framework for an urban canopy layer model
- Untangling the Geometry and Speed for RF Sensing Spectrograms
- History-Conditioned Flow Matching for Probabilistic Dynamics of Tendon-Driven Continuum Robots
- Autoencoders vs. Numerical Analysis--Informed Manifold Learning for Navier--Stokes Flows
- FrFNO: Injecting the analytic Mittag-Leffler propagator into a resolution-robust neural operator for space-time fractional PDEs
- Triply-Scalable Equivariant Gaussian Process Modeling
- Complete Neural Electronic Initialization Accelerates Materials DFT
- Learning Physics from an Imperfect Ancestor: Joint Failure Mode Resolution for Neural Operators and PINNs
- Riemannian Simultaneous Inference for Tangent Vector Field Regression
- Backward log orthogonal functions and their approximation theory
- Enhancing Transformer Representations of Symbolic ODE Expressions
- Estimation and Control of Tensegrity Manipulator Kinematics based on Strut Inclination Angles
- A Low-rank ADI Algorithm for the Numerical Solution of Large Discrete-time Non-symmetric Algebraic Riccati Equations
- Multitask Jet Analysis with Vision-Language Models: A Physics-Informed Four-Panel Representation
- NeuIDO: Neural Intrinsic Dynamics Operator for Physics-Informed 4D World Models
- Continuous Delayed-Memory Stochastic Gradient Descent for Continuous-Time Reinforcement Learning from Astrophysical Time Series
- Integral Chemical Reaction Neural Networks
- Set-Based Value Function Characterization and Neural Approximation of Stabilization Domains for Input-Constrained Discrete-Time Systems
- An Improved Periodic Activation for PINNs Reconstructing Convective Flows
- Periodic Neural Mapping for Unsteady Rotor-Blade Pressure and Aeroelastic Load Prediction
- Gravity-Informed Neural Networks for Post-Newtonian Binary Dynamics
- Physics-constrained Inference of Somatic Dynamics from Dendritic Recordings in Weakly Coupled Two-Compartment Neuron Model
- Droop-Aware Foundation Model Power Flow
- K-TRAIL: Simulator-Guided Generative Design of EM/RF Circuits
- TokaGLINT: A Scalable GPU-Tailored Implicit Solver for Full 3D Tokamak Electromagnetic Simulations
- Comparative analysis of Neural Networks approaches for Initial Orbit Determination of Near-Earth Objects
- Towards Physics-Informed Neural Networks for Stiff Guitar String Vibrations
- ForceTwin: Physics-informed Digital Twins for Robotic Manipulation from Instrumented Human Interaction
- Periodic Neural Mapping for Unsteady Rotor-Blade Pressure and Aeroelastic Load Prediction
- LOInK: Learned Optimal Inverse Kinematics via Structured Neural Surrogate Models
- PIVOT: Physically Informed Vision-Language Off-Road Traversability for Field Robot Navigation
- Amortizing Physics-Informed Neural Solvers via Graph Hypernetworks
- Emulation strategies for Bayesian inference of regional left ventricle material parameters
- Beyond PINNs: A Unified Gauss-Newton and Petrov-Galerkin Framework for Neural and Hybrid PDE Solvers
- Accelerating structural optimization via EIFEM: a ROM-based preconditioner
- Continental-scale probabilistic resistivity imaging of Australia using deep learning: Implications for geology, groundwater, and critical minerals
- Expected Hypervolume Maximization for Multiobjective Optimization under Uncertainties
- Rapidity-Coupled Spin Dynamics in Pulsed Laser Fields from Physics-Informed Neural Networks
- PosteriorBench: From Point Estimates to Posterior Matching in Evaluating Generative Inverse Solvers
- A Physics-Informed Inverse Modeling Framework for Moose-Wolf Dynamics from Limited and Noisy Data
- Physical Knowledge on Historical Data Matters More Than Enforcing Physical Constraints on the Forecast
- Ladder of Information Limits on Prediction for Reduced-Order Models
- Physics-Informed Hemodynamic Modeling for Data-Free Prediction and Sparse-Data Assimilation
- A Highly Scalable Quantized Tensor-Train FDTD Framework for the Simulation of Three-Dimensional Electromagnetic Scattering Problems
- SPUS PDE-UNet-36M-v2 (FNS-KF) PDE Solving Model
- Search at the Cost of Sampling: Nearly-Instant Latent Space Bayesian Optimization
- GPCR Ligand Bioactivity Prediction with Physics-Informed Dual-State Query Learning
- Stable by Construction: Variational Latent Markov Operators for Long-Horizon PDE Prediction
- Structure-Informed Data-Driven Reduced-Order Modeling of Scalar Hyperbolic Conservation Laws via Kinetic Defect Measure
- Calibration of electromagnetic shower features in the CMS calorimeter with machine-learning techniques
- Adaptive and accuracy-aware multiple data assimilation in a three step framework
- Neural Modal Decomposition: Architectural Priors from Observables
- A Variational Optimal Transport Operator on Incompressible Flow
- Vertical Assessment of RF-EMF Exposure in a Building Adjacent to a Multi-Operator Shared Base Station
- Quantum-hardware spectral co-design framework for multifrequency Rydberg electrometry
- A Geometrically Parameterized Quasi-Stationary 3D Model for High-Frequency Induction Tube Welding
- Solar Flare Prediction Using a Hybrid Convolutional Neural Network and Transformer Model
- Expanding RCWA Capabilities with Advanced S-matrix Algorithms
- Anisotropic Maxwell neural operator for rapid parametric full-wave modelling of ion cyclotron resonance heating
- Continually Learning Neural-Operator Surrogate for Three-Dimensional Airborne Electromagnetic Bayesian Inversion
- Physics-Informed Neural Operator Surrogate for 2D Magnetohydrodynamic Reconnection
- The Kuramoto Neural Operator: Learning to Solve PDEs via Coupled Oscillator Dynamics
- ADEx-FNO: A Unified Ambient-Domain Framework for Fourier Neural Operators on Varying Geometries
- PhysicsNeMo: Neural-Operator-Based Physics Simulation Framework
- Physics-Informed Learning Annual Review 2025-2026
- Physics-Informed Token Transformer for Nonlinear Balance Laws: Schwarzschild-Burgers Fluid Flows
- Multilevel Graph Wavelet Compressed Sensing with Scale-Aware Neural Recovery
- An Agentic AI Scientific Community for Automated Neural Operator Discovery
- Fourier Neural Operators for Rayleigh-Bénard Convection
- PRONE: Petrov-Galerkin Operator Learning Unifies DMD, SINDy & Koopmanism
- How Much Memory Do We Need? Adaptive Memory Gate for Neural Operators
- DKEKAN: A Single-Parameterized KAN Surrogate for Drift Kinetic Equation Toward Fast Neoclassical Toroidal Viscosity Torque Modeling in Tokamaks
- Geometry-Aware Anisotropic Boundary Correction for Aerodynamic Simulation
- Physics-informed generative AI for semiconductor manufacturing: Enforcing hard physical constraints in generative models by construction
- GENERIC-FNO: Embedding Energy Conservation and Entropy Production into Fourier Neural Operators
- Advanced Flood Prediction with Physics-Guided Deep Learning: Combining UNet, FNO, and SAR/Optical Imagery
- Validation-Gated Multi-Agent Governance for Online Adaptation of Thermal-Hydraulic Surrogate Models under Operating-Regime Shift
- Neural Operator-Based Surrogate Model for CFD: Helical Coil Steam Generator in Small Modular Reactor
- Transformer-based Neural Operators for 3D Wind Field Prediction over Complex Mountainous Terrain
- Therm-FM: Foundation Model is ALL YOU NEED for 3D-ICs Thermal Simulation
- AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training
- Transolver: A Transformer Solver for Large-Scale Industrial Geometries
- DeepONet (Original Paper)
- Fourier Neural Operator (Original Paper)
- The Well: A Multi-Domain Benchmark for Physics Foundation Models
- Geometry-aware Incremental Neural Operator for Long-Horizon PDE Prediction
- HIPNO: Symmetry-Aware Physics-Informed Neural Operators for Noninvasive Hemodynamic Inference
- DNNsolver: Accurate and Efficient Deep Learning Modeling of Polarization-Sensitive Diffractive Neural Networks
- Koopman-Accelerated Model-Based Diffusion for Real-Time Robot Control
- Mollified-sharp decomposition: a probabilistic regularization of parametric POD for shock-bearing flows
- Spectral shaping of Gaussian white noise for synthetic axion signal generation in microwave cavity haloscopes
- Variational Objectives for Amortized Bayesian Inference in Inverse Problems: The Role of Posterior Conditioning
- Gnomon: Physics-Informed Link-State Forecasting for LEO Networks
- TubeLab: Interactive Inverse Design of Wind Instrument Bores with Hard Spectral Constraints
- Beyond Point Prediction: Artificial Representative Trees with Uncertainty
- FrFNO: Injecting the analytic Mittag-Leffler propagator into a resolution-robust neural operator for space-time fractional PDEs
- A Simplified Model for Linear Mode Coupling in Multimode Fibers with Experimental Assessment
- WaveOp-LiteFM: Lightweight Neural-Operator Flow Matching for Satellite-to-Radar Precipitation Retrieval
- A Nonlinear Physics-based Reduced Order Model with Convolutional-based Operator Compression
- PQLS: A Quasilinear Gyrokinetic Transport Solver with a Bayesian Saturation-Rule Closure
- An improved periodic activation for PINNs reconstructing convective flows
- Beyond Phase Reduction: Amplitude Collapse in Optimal Control of Coupled Oscillators
- One-Step Generative Surrogate Models via Block-Triangular Joint Drifting
Topic Collections (3)
Editor-curated topic collections & learning paths for Physics-AI
Glossary (26)
Bilingual definitions of core Physics-AI / Scientific ML concepts
- Physics-Informed Neural Network
- Neural Operator
- Fourier Neural Operator
- Deep Operator Network
- Graph Neural Operator
- Reduced-Order Model
- Surrogate Model
- Operator Learning
- PDE Residual Loss
- Proper Orthogonal Decomposition
- Multi-Fidelity Modeling
- Differentiable Physics
- Autoregressive Rollout
- Latent Dynamics
- Finite Element Method
- Finite Volume Method
- Computational Fluid Dynamics
- Meshfree Method
- PDE Benchmark
- Uncertainty Quantification
- Extrapolation
- Scientific Machine Learning
- Inverse Problem
- Digital Twin
- Multiphysics Coupling
- Spectral Bias
Paper Digest (2)
Weekly arXiv digest for Physics-AI / Scientific ML, with editorial reasons to read
Industries
Physics-AI resources grouped by industry scenario (Power & Energy, Compute / HPC)
- Power & Energy (9)
- Compute / HPC (16)
- Semiconductor & Photonics (9)
- Robotics & Embodied AI (17)
- Earth & Environment (17)
- Materials & Chemicals (30)
- Aerospace (19)
- Biomedical (10)
- Fusion & Nuclear (8)
- Quantum Tech (13)
- Automotive & Mobility (5)
- Civil & Infrastructure (4)
- High-Energy Physics (6)
- Astronomy & Space (3)