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just-the-docs

A modern, high customizable, responsive Jekyll theme for documentation with built-in search.

kits19-challenge

Kidney Tumor Segmentation Challenge 2019

latex_paper_writing_tips

Tips for Writing a Research Paper using LaTeX

libpku

贵校课程资料民间整理

loss-landscape

Code for visualizing the loss landscape of neural nets

mcnet_pytorch

mixnet-pytorch

A PyTorch Implementation of MixNet

mobilenet

mobilenetv2.pytorch

72.8% MobileNetV2 1.0 model on ImageNet and a spectrum of pre-trained MobileNetV2 models

nasbowl

[ICLR '21] Interpretable Neural Architecture Search using Bayesian Optimisation with Weisfiler-Lehman Kernel (NAS-BOWL)

net2net

Net2Net implementation on PyTorch for any possible vision layers.

net2net.torch

Implementation of http://arxiv.org/abs/1511.05641 that lets one build a larger net starting from a smaller one.

neuralpredictor.pytorch

Open source reproduction in PyTorch of "Neural Predictor for Neural Architecture Search".

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

pa-da

[CVPR '23] PA&DA: Jointly Sampling PAth and DAta for Consistent NAS

paddlepaddle-experience

pdarts

Codes for our paper "Progressive Differentiable Architecture Search:Bridging the Depth Gap between Search and Evaluation"

pedestrian-attribute-recognition-pytorch

A simple baseline for pedestrian attribute recognition in surveillance scenarios

pinat

[AAAI '23] PINAT: A Permutation INvariance Augmented Transformer for NAS Predictor

probabilityhomework

**科学院大学（计算所）《概率方法与随机图》课程作业与教材

pytorch-distributed

A quickstart and benchmark for pytorch distributed training.

pytorch_deepfm

DeepFM for CTR prediction problem （pytorch 1.0）

pytorch_lmdb_imagenet

Use lmdb to speed up imagenet dataset

pytorch_shake_shake

A PyTorch implementation of shake-shake

quiver

Interactive convnet features visualization for Keras

quiverpytorch

Interactive CNN visualization tool for pytorch

recommendersystems

rekcarc-tsc-uht

清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University

rlnas

satnet

See and Think: Disentangling Semantic Scene Completion