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PyTorch implementation of normalizing flow models
This repo contains the code for solving Poisson Equation using Physics Informed Neural Networks
PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
This R package allows the emulation using a mesh-clustered Gaussian process (mcGP) model for partial differential equation (PDE) systems.
Neural Operator-Assisted Computational Fluid Dynamics in PyTorch
[ICLR 2023] Interplay between the Attention and Electrical Impedance Tomography
This is the code of my master thesis.
Learning in infinite dimension with neural operators.
ICON for in-context operator learning
A playbook for systematically maximizing the performance of deep learning models.
Physics Informed Machine Learning Tutorials (Pytorch and Jax)
PyTorch implementation of MAE https//arxiv.org/abs/2111.06377
[Mamba-Survey-2024] Paper list for State-Space-Model/Mamba and it's Applications
Asymptotic-Preserving Neural Networks for Solving Multiscale Kinetic Equations
Zhu-Zhen-Yi / awesome-AI-for-time-series-papers
Forked from qingsongedu/awesome-AI-for-time-series-papersA professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
[TPAMI 2024] Awesome Resources of GNNs for Time Series Analysis (GNN4TS)
A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.
A Matlab/Octave toolbox for stochastic Galerkin methods