MODEL BASED REINFORCEMENT LEARNING FOR BIOLOGICAL SEQUENCE DESIGN
Lucy Colwell - Machine learning for biological sequence design with therapeutic applications
Lucy Colwell (Cambridge), Machine Learning for Biological Sequence Discovery and Design
GFLOWNET: A theorical introduction and application on biological sequences design
SYNB1 - Machine Learning for Protein Design
Machine Learning-based Design of Proteins and Small Molecules
Functional alignment of protein language models via reinforcement learning
Personalization of a Hip Exoskeleton Assistance via Reinforcement Learning
How to design enzymes using generative machine learning models
MIA: Eli Weinstein on Generative models of proteins and genomes; Primer by Alan Amin on Polya trees
Sequential Batch Reactor (SBR) Technology
MIA: Eric Kelsic, Machine-guided capsid engineering for gene therapy; Sam Sinai, Sequence design
AlphaFoldとタンパク質折り畳みを解くグランドチャレンジ
GFlowNets sample distribution via CellularAutomata
Neural Networks Explained in 5 minutes
Jennifer Listgarten: Machine Learning-based Design of Proteins, Small Molecules, and Beyond
Machine Learning for Scientific Discovery | Yoshua Bengio
Yang Shen - Forward Prediction and Reverse Design for Molecular Discovery
Generative AI and Foundation Models in BioPharma. The next frontier.
Machine learning-based design (of proteins, small molecules and beyond) - Jennifer Listgarten
