yilish

SAME

Code for the papers: "Graph Representation Learning for Multi-Task Settings: a Meta-Learning Approach", "A Meta-Learning Approach for Graph Representation Learning in Multi-Task Settings"

meta-learning-qsar

Meta-Learning GNN Initializations for Low-Resource Molecular Property Prediction

FS-Mol

FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot learning research in the domain of molecules and graph-structured data.

HowToTrainYourMAMLPytorch

The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.

wandb_on_slurm

Example of how to use Weights & Biases on Slurm

awesome-molecular-generation

Awesome papers related to generative molecular modeling and design.

GCNDepth

Self-Supervised CNN-GCN Autoencoder for Monocular Depth Estimation

higher

higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.

FAML

Pytorch implementation of Fast Adaptive Meta-Learning for Few-Shot Image Generation (FAML).

awesome-few-shot-gnn

An index of algorithms for few-shot learning/meta-learning on graphs

Awesome-Graph-Prompting

A curated list of resources for graph prompting methods

ChemLLMBench

What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

rxnmapper

RXNMapper: Unsupervised attention-guided atom-mapping. Code complementing our Science Advances publication on "Extraction of organic chemistry grammar from unsupervised learning of chemical reactions" (https://advances.sciencemag.org/content/7/15/eabe4166).

reaction_utils

Utilities for working with datasets of chemical reactions, reaction templates and template extraction.

NERF

Code for our paper Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction (ICML 2021)

FraGAT

FraGAT: a fragment-oriented multi-scale graph attention model for molecular property prediction

tongjithesis

同济大学本科毕业设计LaTeX模板 LaTeX template for Tongji Undergaduate Thesis

awesome-graph-transformer

Papers about graph transformers.

GRACE

[GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)

awesome-self-supervised-learning-for-graphs

A curated list for awesome self-supervised learning for graphs.

VGAE_pyG

An VGAE implementation using pytorch geometric.

GraphXAI

GraphXAI: Resource to support the development and evaluation of GNN explainers

info-nce-pytorch

PyTorch implementation of the InfoNCE loss for self-supervised learning.

pretrain-gnns

Strategies for Pre-training Graph Neural Networks

TokyuSurvival

A Visual Novel Game

poincare-embeddings

PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"

Gene2vec

Gene2Vec: Distributed Representation of Genes Based on Co-Expression

onto2vec

Representation learning for ontologies and their annotations

NeurIPS-CellSeg

Naive baseline for microscopy image segmentation challenge in NeurIPS 2022

HiG2Vec