Все публикации

Physics-Informed Holomorphic Neural Networks (PIHNNs) || Oct 25, 2024

AttnPINNs || Improving Spectral Bias in Neural Operators || SympGNNs || Oct 18, 2024

A Gaussian Process and Input Encoding for Operator Learning || Topology Optimization || Oct 11, 2024

Reconstructing Turbulent Multi-Phase Flow || Oct. 4, 2024

Nonlocal Turbulence Models with NNs || Sep 27, 2024

PINNs for magnetostatic field simulation || Safe ML via Embedded Over approximation || Sep 20, 2024

Multi-Fidelity Modeling for Structural Dynamics || Sep. 6, 2024

Martingale Neural Network || Aug. 30, 2024

Isogeometric analysis and deep operator learning || Neural PDEs for Robot Motion || Aug. 23, 2024

A Resolution Independent Neural Operator || Aug 16, 2024

Simulating large-scale from the molecular scale with machine learning || Aug 9, 2024

KFAC for PINNs || Aug 2, 2024

Multiscale particle simulation || Bind the Cross-Section of Returns || July 26, 2024

PINNs in dynamic linear elasticity || DeepONet for 3D field predictions || Seminar on July 12, 2024

Unconstrained minimization for regression|| Sampling with Langevin Dynamics||Seminar on July 5, 2024

Simulation-Calibrated SciML || HPINNs: You need curvature! || Seminar on June 28, 2024

FastVPINNs || Seminar on June 21, 2024

Score-based Diffusion Models || Seminar on June 14, 2024

Mathematical Foundations of Deep Learning for PDEs || Seminar on June 7, 2024

optimization process of PINNs|| Deep Information Bottleneck || Seminar on May 31, 2024

Physics-enhanced deep surrogate models|| Universal-PINNs for QSP || Seminar on May 24, 2024

Spatiotemporal Learning of Cell Fate||Discovering slow manifolds with PINNs||Seminar on May 10, 2024

Integrating PDE operators into NN architecture || Seminar on May 3, 2024

Structure-conforming Operator Learning||Diffusion Models and PDE solvers|| Seminar on April 26, 2024