cyberpunk_chen's Projects
Atomistic Line Graph Neural Network
Must-read papers and resources related to causal inference and machine (deep) learning
Crystal graph convolutional neural networks for predicting material properties.
Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov
数据科学竞赛知识、代码、思路
Conditional diffusion model to generate MNIST. Minimal script. Based on 'Classifier-Free Diffusion Guidance'.
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被全球200所大学采用教学。
A methodology to transform a non-image data to an image for convolution neural network architecture
This repository contains implementations and illustrative code to accompany DeepMind publications
a very similar work with crydiff on the base diffusion model
Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
A pytorch implemention of GCN-GAN for temporal link prediction.
Must-read papers on graph foundation models (GFMs)
《深入浅出图神经网络:GNN原理解析》配套代码
This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".
Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.
Shared repo for trajectory analysis and infrastructure development
首先是中文的翻译啦,然后是模型用到中文上面
PyTorch code for "Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions"
Simple yet efficient algorithms for Link Prediction in Dynamic Graphs
LVDM: Latent Video Diffusion Models for High-Fidelity Long Video Generation
An evaluation framework for machine learning models simulating high-throughput materials discovery.
Tutorial of GNN Dynamics, WSDM' 2023
Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction
👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)