Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

• Meta-learning Hybrid Spiking networks as physics-based nonlinear solvers for physical simulations

  2026 npj Unconventional Computing article Engineering Advanced Memory and Neural Computing Open access

  1

  citations
• Finite Operator Learning: Bridging neural operators and numerical methods for efficient parametric solution and optimization of PDEs

  2025 Finite Elements in Analysis and Design article Physics and Astronomy Model Reduction and Neural Networks

  10

  citations
• Digitalizing metallic materials from image segmentation to multiscale solutions via physics informed operator learning

  2025 npj Computational Materials article Materials Science Machine Learning in Materials Science Open access

  7

  citations
• A Finite Operator Learning Technique for Mapping the Elastic Properties of Microstructures to Their Mechanical Deformations

  2024 International Journal for Numerical Methods in Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access

  27

  citations
• Brain-inspired spiking neural networks in Engineering Mechanics: a new physics-based self-learning framework for sustainable Finite Element analysis

  2024 Engineering With Computers article Physics and Astronomy Model Reduction and Neural Networks Open access

  12

  citations
• Physics-Based Self-Learning Spiking Neural Network enhanced time-integration scheme for computing viscoplastic structural finite element response

  2024 Computer Methods in Applied Mechanics and Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access

  13

  citations
• Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations

  2023 Geoscientific model development article Physics and Astronomy Model Reduction and Neural Networks Open access

  39

  citations
• Reply on RC2

  2023 peer-review Physics and Astronomy Model Reduction and Neural Networks Open access

  0

  citations
• Comment on gmd-2022-309

  2023 peer-review Physics and Astronomy Model Reduction and Neural Networks Open access

  0

  citations
• Reply on CEC1

  2023 peer-review Physics and Astronomy Model Reduction and Neural Networks Open access

  0

  citations
• Reply on AC2

  2023 peer-review Physics and Astronomy Model Reduction and Neural Networks Open access

  0

  citations
• Reply on RC1

  2023 peer-review Physics and Astronomy Model Reduction and Neural Networks Open access

  0

  citations
• Comment on gmd-2022-309

  2023 peer-review Physics and Astronomy Model Reduction and Neural Networks Open access

  0

  citations
• Perspectives of Physics-Based Machine Learning for Geoscientific Applications Governed by Partial Differential Equations

  2023 preprint Physics and Astronomy Model Reduction and Neural Networks Open access

  5

  citations
• Spline-PINN: Approaching PDEs without Data Using Fast, Physics-Informed Hermite-Spline CNNs

  2022 Proceedings of the AAAI Conference on Artificial Intelligence conference-paper Physics and Astronomy Model Reduction and Neural Networks Open access cited by 1 patent

  60

  citations
• HybridML: Open source platform for hybrid modeling

  2022 Computers & Chemical Engineering article Computer Science Modeling and Simulation Systems Open access

  30

  citations
• SOLVING TRANSIENT INVERSE HEAT TRANSFER PROBLEMS IN COMPLEX GEOMETRIES USING PHYSICS-GUIDED NEURAL NETWORKS (PGNN)

  2021 MM Science Journal article Physics and Astronomy Model Reduction and Neural Networks Open access

  2

  citations

17 results