Yifu Hu's starred repositories
transformers
๐ค Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
annotated_deep_learning_paper_implementations
๐งโ๐ซ 60+ Implementations/tutorials of deep learning papers with side-by-side notes ๐; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ๐ฎ reinforcement learning (ppo, dqn), capsnet, distillation, ... ๐ง
instant-ngp
Instant neural graphics primitives: lightning fast NeRF and more
sentence-transformers
Multilingual Sentence & Image Embeddings with BERT
attention-is-all-you-need-pytorch
A PyTorch implementation of the Transformer model in "Attention is All You Need".
nerf-pytorch
A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.
dcgan_code
Deep Convolutional Generative Adversarial Networks
occupancy_networks
This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"
natural-questions
Natural Questions (NQ) contains real user questions issued to Google search, and answers found from Wikipedia by annotators. NQ is designed for the training and evaluation of automatic question answering systems.
PointSetGeneration
Code for ``A Point Set Generation Network for 3D Object Reconstruction from a Single Image''
densenet-pytorch
A PyTorch Implementation for Densely Connected Convolutional Networks (DenseNets)
VirtualCapsuleEndoscopy
VR-Caps: A Virtual Environment for Active Capsule Endoscopy
ObjectFolder
ObjectFolder Dataset
MSMARCO-Conversational-Search
Truly Conversational Search is the next logic step in the journey to generate intelligent and useful AI. To understand what this may mean, researchers have voiced a continuous desire to study how people currently converse with search engines. Traditionally, the desire to produce such a comprehensive dataset has been limited because those who have this data (Search Engines) have a responsibility to their users to maintain their privacy and cannot share the data publicly in a way that upholds the trusts users have in the Search Engines. Given these two powerful forces we believe we have a dataset and paradigm that meets both sets of needs: A artificial public dataset that approximates the true data and an ability to evaluate model performance on the real user behavior. What this means is we released a public dataset which is generated by creating artificial sessions using embedding similarity and will test on the original data. To say this again: we are not releasing any private user data but are releasing what we believe to be a good representation of true user interactions.
hyper-kvasir
GitHub repository for the Hyper-Kvasir dataset.
LDPolypVideo-Benchmark
A public endoscopic video dataset for polyp detection
aws-sagemaker-custom-jupyter-kernel
This repo provides a couple of easy-to-use template scripts to help you set up a custom jupyter kernel on a AWS Sagemaker Jupyter Notebook Instance.