Yicheng Jin's repositories
DeepLearningExamples
Deep Learning Examples
AMC
[ECCV 2018] PyTorch implementation for AMC: AutoML for Model Compression and Acceleration on Mobile Devices.
awd-lstm-lm
LSTM and QRNN Language Model Toolkit for PyTorch
CUDALibrarySamples
CUDA Library Samples
distiller
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://nervanasystems.github.io/distiller
FairNAS
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search
HAQ
[CVPR 2019, oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision
incubator-tvm
Open deep learning compiler stack for cpu, gpu and specialized accelerators
lightweight-human-pose-estimation.pytorch
Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.
NAS
Neural architecture search(NAS)
nlp-architect
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
nobel-nomination-viz
Visualization of Nobel nominations with Javascript and D3.js
openpose_train
Training repository for OpenPose
openposeFPGA_mobilenet
This is an HLS-based FPGA accelerator implementation for openpose application.
perftest
Infiniband Verbs Performance Tests
PocketFlow
An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.
ProxylessNAS-1
[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware.
pytorch-cifar
95.16% on CIFAR10 with PyTorch
pytorch-tensorrt
pytorch model tensorrt inference code
reaver
Reaver: Modular Deep Reinforcement Learning Framework. Focused on StarCraft II. Supports Gym, Atari, and MuJoCo. Matches reference results.
tf-pose-estimation
Deep Pose Estimation implemented using Tensorflow with Custom Architectures for fast inference.
transformers
🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.