heany

How-To-Ask-Questions-The-Smart-Way

本文原文由知名 Hacker Eric S. Raymond 所撰寫，教你如何正確的提出技術問題並獲得你滿意的答案。

deskreen

Deskreen turns any device with a web browser into a secondary screen for your computer. ⭐️ Star to support our work!

pytorch-cnn-visualizations

Pytorch implementation of convolutional neural network visualization techniques

pdfplumber

Plumb a PDF for detailed information about each char, rectangle, line, et cetera — and easily extract text and tables.

aria2.sh

Aria2 一键安装管理脚本 增强版

loss-landscape

Code for visualizing the loss landscape of neural nets

Metaworld

Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning

vega

AutoML tools chain

multi-task-learning-example

A multi-task learning example for the paper https://arxiv.org/abs/1705.07115

ACNet

ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks

pytorch-segmentation-detection

Image Segmentation and Object Detection in Pytorch

fair_self_supervision_benchmark

Scaling and Benchmarking Self-Supervised Visual Representation Learning

Aspect-Based-Sentiment-Analysis

A paper list for aspect based sentiment analysis.

Lottery-Ticket-Hypothesis-in-Pytorch

This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adapted to any model/dataset.

NSFC-LaTex

swapping-autoencoder-pytorch

Unofficial implementation of Swapping Autoencoder for Deep Image Manipulation (https://arxiv.org/abs/2007.00653) in PyTorch

DeepLab-v3-plus-cityscapes

mIOU=80.02 on cityscapes. My implementation of deeplabv3+ (also know as 'Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation' based on the dataset of cityscapes).

deeplab_v2

基于v2版本的deeplab,使用VGG16模型，在VOC2012，Pascal-context，NYU-v2等多个数据集上进行训练

AdaShare

AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning

AuxiLearn

Official implementation of Auxiliary Learning by Implicit Differentiation [ICLR 2021]

RoutingNetworks

progre.sh

Progress bar (loading, process) to a shell script (bash, console, terminal).

Dynamic_multi-task-learning

Multi-Task Learning Using Dynamic Weights of Tasks for Face Recognition withFacial Expression

fasterai1

FasterAI: A repository for making smaller and faster models with the FastAI library.

dauphin

An uncertainty-based random sampling algorithm for data augmentation

PCGrad-PyTorch

PyTorch implementation for "Gradient Surgery for Multi-Task Learning" https://arxiv.org/abs/2001.06782

TVOS

使用Django搭建的数据可视化项目，详细见doc文档和readme

visdom_logger

Wrapper to use visdom as logger when training ML models

iterative-pruning-reinit

MrRCE

Official implementation of Capturing Between-Tasks Covariance and Similarities Using Multivariate Linear Mixed Models [EJS 2020]