A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)

List of computational protein design research labs

g2o: A General Framework for Graph Optimization

IntelliJ IDEA Community Edition & IntelliJ Platform

List of papers about Proteins Design using Deep Learning

Курс по глубинному обучению для графовых данных преподаваемый на ФКН ВШЭ

n³ The unorthodox terminal file manager

A short course on proteins and protein design aimed at early career students

Implementation of Diffusion Transformer (DiT) in JAX

The official PyTorch implementation of Google's Gemma models

Let us control diffusion models!

Guide for fine-tuning Llama/Mistral/CodeLlama models and more

Materials for the Deep Learning 2 course at HSE AMI

Data science interview questions with answers. Not ideally (yet)

Normalizing flows in PyTorch. Current intended use is education not production.

Scripts for fine-tuning Meta Llama with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supporting…

A library for efficient similarity search and clustering of dense vectors.

Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

Graph Neural Network Library for PyTorch

gnn explainer

Must-read papers on graph neural networks (GNN)

A collection of resources and papers on Diffusion Models

fast-stable-diffusion DreamBooth

Denoising Diffusion Probabilistic Models

Course about deep learning for computer vision and graphics co-developed by YSDA and Skoltech.