Molecular Generation

Survey

• A survey of generative AI for de novo drug design: new frontiers in molecule and protein generation (Briefings in Bioinformatics 2024) [paper]

Papers

2024

• Learning Joint 2-D and 3-D Graph Diffusion Models for Complete Molecule Generation (TNNLS 2024)[paper]
• Domain-Agnostic Molecular Generation with Self-feedback (ICLR 2024)[paper][code]
• Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models (ICLR 2024)[paper][code]

2023

• Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation (NeurIPS 2023)[paper][code]
• ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling (Nat. Mach. Intell 2023)[paper][code]
• Geometric Latent Diffusion Models for 3D Molecule Generation (PMLR 2023)[paper][code]
• MDM:Molecular Diffusion Model for 3D Molecule Generation (AAAI 2023)[paper][code]
• Equivariant 3D-conditional diffusion model for molecular linker design (Nat. Mach. Intell 2023)[paper][code]
• Molecule generation using transformers and policy gradient reinforcement learning (Sci. Rep 2023)[paper][code]
• Geometry-Complete Diffusion for 3D Molecule Generation and Optimization (ICLR MLDD 2023 & Nature CommsChem 2023)[paper][code]
• SILVR: Guided Diffusion for Molecule Generation (ACS 2023)[paper][code]
• Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation (ACS 2023)[paper][code]
• Deep Generative Models in De Novo Drug Molecule Generation (JCIM 2023)[paper]
• Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation (ACS 2023)[paper][code]
• Multi-modal molecule structure–text model for text-based retrieval and editing (Nat. Mach. Intell 2023)[paper][code]
• LLamol: A Dynamic Multi-Conditional Generative Transformer for De Novo Molecular Design (Nat. Mach. Intell 2023)[paper][code]
• GraphGPT: A Graph Enhanced Generative Pretrained Transformer for Conditioned Molecular Generation (J Cheminform 2023)[paper][code]

2022

• Equivariant Diffusion for Molecule Generation in 3D (PMLR2022)[paper]
• MolGPT:MolecularGenerationUsingaTransformer-DecoderModel (JCIM2022)[paper][code]

2021

• Learning Neural Generative Dynamics for Molecular Conformation Generation (ICLR2021)[paper][code]
• Multi-constraint molecular generation based on conditional transformer, knowledge distillation and reinforcement learning (Nat. Mach. Intell 2021)[paper][code]
• Controlled molecule generator for optimizing multiple chemical properties(Nat. Mach. Intell 2021)[paper][code]
• Masked graph modeling for molecule generation (Nat. Commun 2021)[paper][code]
• Graph Polish: A Novel Graph Generation Paradigm for Molecular Optimization (TNNLS 2021)[paper]
• A deep generative model for molecule optimization via one fragment modification (Nat. Mach. Intell 2021)[paper][code]
• Learning Gradient Fields for Molecular Conformation Generation (ICML 2021)[paper][code]
• GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles (NeurIPS 2021)[paper][code]

2020

• Rethinking Experience Replay: a Bag of Tricks for Continual Learning(ICPR, 2020) [paper] [code]

2019

2018

• Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules (ACs Cent. sci. 2018)[paper]
• Junction Tree Variational Autoencoder for Molecular Graph Generation (PMLR 2018)[paper]
• Syntax-directed variational autoencoder for structured data (ICLR 2018)[paper][code]

2017

• Grammar variational autoencoder (ICCV2017) [paper][code]

2016

Awesome Long-Tailed Recognition / Imbalanced Learning

Find it interesting that there are more shared techniques than I thought for incremental learning (exemplars-based).

Datasets

An Open Community of Researchers and Enthusiasts on Continual/Lifelong Learning for AI

Workshops

4th Lifelong Learning Workshop at ICML 2020

Challenges or Competitions

1st Lifelong Learning for Machine Translation Shared Task at WMT20 (EMNLP 2020)

Feel free to contact me if you find any interesting paper is missing.

Workshop papers are currently out due to space.