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Large Language Models as Molecular Design Engines

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Diagnosing and fixing common problems in Bayesian optimization for molecule design

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Enhancing Generative Molecular Design via Uncertainty-guided Fine-tuning of Variational Autoencoders

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Saturn: Sample-efficient Generative Molecular Design using Memory Manipulation

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AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application

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Enhancing molecular design efficiency: Uniting language models and generative networks with genetic algorithms

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FragGT: Fragment-based evolutionary molecule generation with gene types

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Generation of Chemical Space of Compounds for Prostate Cancer Treatment: Biological Activity Prediction, Clustering, and Visualization of Chemical Space

Molecule Design by Latent Prompt Transformer

Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation

Language models in molecular discovery

A molecule perturbation software library and its application to study the effects of molecular design constraints

Expanding the chemical space using a Chemical Reaction Knowledge Graph

Transformer-Based Molecular Generative Model for Antiviral Drug Design

Interactive Molecular Discovery with Natural Language

Molecular Descriptors, Structure Generation, and Inverse QSAR/QSPR Based on SELFIES

Molecule generation using transformers and policy gradient reinforcement learning

MolXPT: Wrapping Molecules with Text for Generative Pre-training