Collection of papers for Molecular Representation using AI

Self-supervised learning of molecular representations from millions of tandem mass spectra using DreaMS (Nat Biotechnology)

C-GRAN (Community-Guided Recursive Annotation Network) is an open, network-based framework for the systematic discovery and annotation of emerging structural analogs in complex environmental samples.

The official source code of "MagiNet: Mask-Aware Graph Imputation Network for Incomplete Traffic Data"

An awesome project on irregular time series and incomplete time series

This repository implements an automated crawling tool for topics about "data mining" papers from the arXiv preprint website.

[KDD 2025] Awesome Multi-modal Time Series Analysis

AceParse: A Comprehensive Dataset with Diverse Structured Texts for Academic Literature Parsing

Daily ArXiv Papers.

This project aims to collect the latest "call for reviewers" links from various top CS/ML/AI conferences/journals

This repository collects papers related to the application of AI in Environmental Science.

The code repo of Jingwei, reconstructing global ocean oxygen changes with hybrid graph learning.

A collection of transformer-based models and developmental scripts presented in the publication "Transformers enable accurate prediction of acute and chronic chemical toxicity in aquatic organisms".

MassSpecGym: A benchmark for the discovery and identification of molecules (NeurIPS 2024 Spotlight)

This is an improved MetFrag algorithm for molecular annotation of environmental pollutants.

Efficiently predicting high resolution mass spectra with graph neural networks

Tandem Mass Spectrum Prediction with Graph Transformers

Official PyTorch implementation of SWave

The official source code of MTSCI: A Conditional Diffusion Model for Consistent Imputation in Incomplete Time Series

generative model: autoencoder, gan, ddpm

graph neural network library

A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery (EMNLP'24)

Official code, datasets and checkpoints for "Timer: Generative Pre-trained Transformers Are Large Time Series Models" (ICML 2024) and subsequent works

FNSPID: A Comprehensive Financial News Dataset in Time Series

Official implementation of TGTSF in "Beyond Trend and Periodicity: Guiding Time Series Forecasting with Textual Cues"

Build high-performance AI models with modular building blocks