A challenge to explore adversarial robustness of neural networks on MNIST.

This is the github repository of the project of overcoming simplicity bias in deep neural networks

The open-source tool for building high-quality datasets and computer vision models

Existing Literature about Machine Unlearning

Solution to CS231n Assignments 2019

Google Research

Official implementation "ChipNet: Budget-Aware Pruning with Heaviside Continuous Approximations"

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

Code Repository for Covid Vaccine Distribution system

Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)

Summarize Massive Datasets using Submodular Optimization

Trax — Deep Learning with Clear Code and Speed

Brain Segmentation on MRBrains18

List of AI Residency Programs

Official Implementation "Rescaling CNN through Learnable Repetition of Network Parameters"

torch-optimizer -- collection of optimizers for Pytorch

PyTorch Computer Vision Cookbook, Published by Packt

Accompanying code for the paper "Object Detection Neural Network Improves Fourier Ptychographic Reconstruction"

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

9th Place Solution of Kaggle Global Wheat Detection

Data science interview questions and answers

Run VSCode (codeserver) on Google Colab or Kaggle Notebooks

starter from "How to Train a GAN?" at NIPS2016

Research papers with annotations, illustrations and explanations

1st place solution to EAD 2020 (segmentation track) (https://ead2020.grand-challenge.org/)

Meshery, the cloud native manager

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

DeepLab-ResNet rebuilt in Pytorch