acse-sl420

acse-sl420's Stars

• pg2455/KAN-Tutorial

  Understanding Kolmogorov-Arnold Networks: A Tutorial Series on KAN using Toy Examples

  Language:Jupyter Notebook1088

• camlab-ethz/AI_Science_Engineering

  This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.

  Language:Jupyter Notebook162

• camlab-ethz/poseidon

  Code for the paper "Poseidon: Efficient Foundation Models for PDEs"

  Language:Python615

• Chen-Cai-OSU/MPNN-GT-Connection

  Language:Python161

• CCSI-Toolset/MGN

  MeshGraphNets (MGN)

  Language:Python5922

• KindXiaoming/pykan

  Kolmogorov Arnold Networks

  Language:Jupyter Notebook13.6k1.2k

• NiklasFreymuth/ASMR

  Adaptive Swarm Mesh Refinement

  Language:Python13

• jdb78/pytorch-forecasting

  Time series forecasting with PyTorch

  Language:Python3.7k599

• XiaoxinHe/Graph-ViT-MLPMixer

  Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"

  Language:Python13921

• wehos/awesome-graph-transformer

  Papers about graph transformers.

  69259

• rasbt/LLMs-from-scratch

  Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step

  Language:Jupyter Notebook21.3k2.1k

• LinXueyuanStdio/PyTorch-DDPM

  500 行代码实现降噪扩散模型 DDPM，干净无依赖

  Language:Jupyter Notebook11311

• Eydcao/BSMS-GNN

  Language:Python456

• sbarwey/interpretable_gnn

  Language:Python42

• qitianwu/SGFormer

  The official implementation for NeurIPS2023 paper "SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations"

  Language:Python19513

• luis-mueller/probing-graph-transformers

  Code for our paper "Attending to Graph Transformers"

  Language:Python708

• lucidrains/iTransformer

  Unofficial implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group

  Language:Python37129

• HinokiBAI/NASA_Li-ion_Battery_SOH_Prediction_with_MVIP-Trans

  This research provides a prognostic framework for off-line SOH estimation of Li-ion battery. With a CNN-Transformer architecture, this program is capable of modeling the temporal correlations of battery signals from both local and global views. In this way, the learning ability of both local features and long period contexts will be enhanced.

  Language:Python608

• Zeyu-Zhu/TFDSUNet

  TFDSUNet: Time-Frequency Dual-Stream Uncertainty Network for Battery SOH/SOC Prediction

  Language:Python316

• iaifi/summer-school-2023

  Language:Jupyter Notebook2113

• XieResearchGroup/Physics-aware-Multiplex-GNN

  Code for our Nature Scientific Reports paper "A universal framework for accurate and efficient geometric deep learning of molecular systems"

  Language:Python5010

• aesabattery/Charging-Curve-Prediction

  Language:Python4315

• stathius/sd-vae

  Code for the paper "Disentangled Generative Models for Robust Prediction of System Dynamics"

  Language:Jupyter Notebook143

• dvgodoy/dl-visuals

  Over 200 figures and diagrams of the most popular deep learning architectures and layers FREE TO USE in your blog posts, slides, presentations, or papers.

  1.3k111

• benmoseley/DLSC-2023

  ETH Zürich Deep Learning in Scientific Computing Master's course 2023

  Language:Jupyter Notebook8619

• LiamMa/GRIT

  This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".

  Language:Python819

• qitianwu/awesome-graph-ood

  Papers about out-of-distribution generalization on graphs.

  51

• kaist-silab/awesome-graph-pde

  Collection of resources about partial differential equations, graph neural networks, deep learning and dynamical system simulation

  846

• BenGutteridge/DRew

  Language:Python293

• MatthieuDarcy/KernelsOperatorLearning

  Language:Jupyter Notebook73