There are 9 repositories under ai4science topic.
Graphormer is a general-purpose deep learning backbone for molecular modeling.
A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
Code and datasets for paper "K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization" in WSDM-2024
A comprehesive survey about foundation models for weather and cliamte data understanding.
What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks
Recent advancements propelled by large language models (LLMs), encompassing an array of domains including Vision, Audio, Agent, Robotics, and Fundamental Sciences such as Mathematics.
List of Geometric GNNs for 3D atomic systems
[ICLR 2022] The implementation for the paper "Equivariant Graph Mechanics Networks with Constraints".
Official code repo for the paper "LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale, Comprehensive, High-Quality Instruction Tuning Dataset"
Must-read papers on NLP for science.
A web app and Python API for multi-modal RAG framework to ground LLMs on high-fidelity materials informatics. An agentic materials scientist powered by @materialsproject, @langchain-ai, and @openai
The official code for "TaxDiff: Taxonomic-Guided Diffusion Model for Protein Sequence Generation"
ImageMol is a molecular image-based pre-training deep learning framework for computational drug discovery.
[NeurIPS 2023] This is the official code for the paper "TPSR: Transformer-based Planning for Symbolic Regression"
A curated list of awesome AI and Bioinformatics.
[ICLR 2024 Spotlight] This is the official code for the paper "SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training"
MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation
AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)
[AAAI 2023] The implementation for the paper "Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs"
Synthetic lethality (SL) is a promising gold mine for the discovery of anti-cancer drug targets. KG4SL is the first graph neural network (GNN)-based model that uses knowledge graph for SL prediction.
AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control
[ICLR'24] "DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training" by Aochuan Chen*, Yimeng Zhang*, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
The official code for "Deep peak property learning for efficient chiral molecules ECD spectra prediction"
[KDD 2024] Papers about deep learning in epidemic modeling.
Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model (NeurIPS 2023 Poster)
Uncover meaningful structures of latent spaces learned by generative models with flows!
[NeurIPS 2022] The implementation for the paper "Equivariant Graph Hierarchy-Based Neural Networks".
Sunwoda Electronic Co., Ltd, and Tsinghua Berkeley Shenzhen Institute (TBSI) generate the TBSI Sunwoda Battery Dataset. We open-source this dataset to inspire more data-driven novel material verification, battery management research and applications.
This is the official repo for the paper "LLM-SR" on Scientific Equation Discovery and Symbolic Regression with LLMs
GPT (Generative Pre-trained Transformer) for de novo molecular design by enforcing specified targets