Stars
A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
A codebase that makes differentially private training of transformers easy.
A detailed summary of "Designing Machine Learning Systems" by Chip Huyen. This book gives you and end-to-end view of all the steps required to build AND OPERATE ML products in production. It is a m…
Training PyTorch models with differential privacy
Latex code for making neural networks diagrams
Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.
The Implementation of Attention Mechanism Enhanced Kernel Prediction Networks in PyTorch.
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
Collection of popular and reproducible image denoising works.
My best practice of training large dataset using PyTorch.
Learning to See in the Dark. CVPR 2018
a reimplementation of PWC-Net in PyTorch that matches the official Caffe version
PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume, CVPR 2018 (Oral)
PyTorch package for the discrete VAE used for DALL·E.
📷 RAW image processing for Python, a wrapper for libraw
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
A curated list of awesome neural radiance fields papers
Supervised Raw Video Denoising with a Benchmark Dataset on Dynamic Scenes. CVPR 2020
Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute
Real-World Super-Resolution via Kernel Estimation and Noise Injection
NVIDIA's Deep Imagination Team's PyTorch Library
😎 A curated list of awesome GitHub Profile which updates in real time
A library for ML benchmarking. It's powerful.
Code for deep generative prior (ECCV2020 oral)