Molecular design
A curated collection of research papers on molecular and material design using generative AI and deep learning techniques.
What is Molecular design?
Papers for Molecular Design using DL is a curated GitHub repository that collects and organizes academic papers on applying generative artificial intelligence and deep learning to molecular and material design. It serves as a structured knowledge base for researchers exploring AI-driven approaches in drug discovery, molecular conformation generation, and material science.
AI researchers, computational chemists, drug discovery scientists, and graduate students working at the intersection of machine learning and molecular design who need a comprehensive, organized reference of current literature.
It saves researchers significant time by providing a pre-organized, community-maintained collection of papers with logical categorization, eliminating the need to manually search and compile literature from disparate sources.
Overview
List of Molecular and Material design using Generative AI and Deep Learning
Use Cases
Best For
- Finding recent papers on diffusion models for molecular conformation generation
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