soumbane

STSGT

Official PyTorch implementation of Spatial-Temporal Synchronous Graph Transformer network (STSGT) for COVID-19 forecasting

Deep_Relational_Reasoning_Epilepsy

Official TensorFlow implementation of Deep Relational Reasoning for prediction of language impairments and seizure outcomes

DualSelfDistillation

Official PyTorch implementation of Dual Self-Distillation (DSD) in U-shaped Networks for Medical Image Segmentation

magmsforEZprediction

Official PyTorch implementation of Sequence-Agnostic Model with Cross-Sequence Distillation for SOZ Localization

annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

attention-is-all-you-need-paper

Implementation of Vaswani, Ashish, et al. "Attention is all you need." Advances in neural information processing systems. 2017.

Awesome-Diffusion-Models

A collection of resources and papers on Diffusion Models

Awesome-Diffusion-Models-in-Medical-Imaging

Diffusion Models in Medical Imaging

soumbane.github.io

Personal Website

tcav

Code for the TCAV ML interpretability project

cav-keras

Concept activation vectors for Keras

cs224w-slides-to-code

CV_notebooks

Set of Jupyter Notebooks linked to Roboflow Blogpost and used in our YouTube videos.

Deep-Learning-In-Production-1

Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.

Diffusion-Models-in-Vision-A-Survey

This repository categorizes the papers about diffusion models applied in computer vision according to their target task. The classifcation is based on our survey: https://arxiv.org/abs/2209.04747v1

fastbook

The fastai book, published as Jupyter Notebooks

GenerativeModels

MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications

Graph_Sampling

Graph Sampling is a python package containing various approaches which samples the original graph according to different sample sizes.

histocartography

Histocartography is a framework bringing together AI and Digital Pathology

iMIMIC-RCVs

This repository contains the code for implementing Bidirectional Relevance scores for Digital Histopathology, which was used for the results in the iMIMIC workshop paper: Regression Concept Vectors for Bidirectional Explanations in Histopathology

LiteratureDL4Graph

A comprehensive collection of recent papers on graph deep learning

machine-learning-interview-enlightener

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

Made-With-ML

Learn how to design, develop, deploy and iterate on production-grade ML applications.

MedicalZooPytorch

A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

Multi-Scale-1D-ResNet

pytorch code of multi scale 1d resnet, we hope it will help your research

pytorch-GAT

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing otherwise seemingly hard concepts.

pytorch_geometric

Graph Neural Network Library for PyTorch

pytorch_geometric_temporal

A Temporal Extension Library for PyTorch Geometric

Sherlock

This repository contains experiments for different publications at the intersection of Computer Vision and Computer Security.

system-design-primer

Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.