Graphormer is a general-purpose deep learning backbone for molecular modeling.
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Updated
May 17, 2024 - Python
Graphormer is a general-purpose deep learning backbone for molecular modeling.
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
ImageMol is a molecular image-based pre-training deep learning framework for computational drug discovery.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)
A Curated List of Language Models in Scientific Domains
A comprehesive survey about foundation models for weather and cliamte data understanding.
Code and datasets for paper "K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization" in WSDM-2024
A curated list of awesome AI and Bioinformatics.
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.
Geom3D: Geometric Modeling on 3D Structures, NeurIPS 2023
[NeurIPS 2023] This is the official code for the paper "TPSR: Transformer-based Planning for Symbolic Regression"
ChatCell: Facilitating Single-Cell Analysis with Natural Language
MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation
List of Geometric GNNs for 3D atomic systems
[ICLR 2022] The implementation for the paper "Equivariant Graph Mechanics Networks with Constraints".
[AAAI 2023] The implementation for the paper "Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs"
What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks
Must-read papers on NLP for science.
Recent advancements propelled by large language models (LLMs), encompassing an array of domains including Vision, Audio, Agent, Robotics, and Fundamental Sciences such as Mathematics.
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