Diffusion-Models-Reading-Group-Fall-2023

This repository will hold the papers, notes, and other materials for the diffusion models reading group in Fall 2023.

About the reading group

This reading group will meet weekly in 3120B Torgersen Hall every Thursday from 3:30 PM to 4:30 PM. The focus is to learn and discuss diffusion models with particular interest in their application of the inference/prediction/design of biomolecules. We will read (approximatley) one paper per week and take turns starting giving short presentations. Presentations will be 30-45 minutes long and will go over the details and results of the paper. We will then use the remaining time to ask questions and have imformal discussions.

Schedule

Date	Presenter	Paper(s)	Notes	Recording
10/26/2023	Trevor Norton	Deep Unsupervised Machine Learning using Nonequilibrium Thermodynamics Denoising Diffusion Probabilistic Models	Slides	Recording
11/2/2023	Trevor Norton	Generative Modeling by Estimating the Gradients of the Data Distribution Score-based Generative Modeling through Stochastic Differential Equations	Slides	Recording
11/9/2023	Nabayan Chaudhury	Diffusion Probabilistic Modeling of Protein Backbones in 3D for the Motif-Scaffolding Problem	Slides	Recording
11/16/2023	Bernard Moussad	Protein Structure Generation via Folding Diffusion	Slides	Recording
11/30/2023	Trevor Norton	DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking	Slides	Recording
12/7/2023	Trevor Norton	Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics