z2007c Goto Github PK

cramer-gan

Tensorflow Implementation on "The Cramer Distance as a Solution to Biased Wasserstein Gradients" (https://arxiv.org/pdf/1705.10743.pdf)

deep-svdd-pytorch

A PyTorch implementation of the Deep SVDD anomaly detection method

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

graphnn

Training computational graph on top of structured data (string, graph, etc)

mmaml-classification

An official PyTorch implementation of “Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation” (NeurIPS 2019) by Risto Vuorio*, Shao-Hua Sun*, Hexiang Hu, and Joseph J. Lim

neuralpointprocess

optimal-transport

A collection of adaptive sparse multi-scale solvers for optimal transport and related optimization problems.

pot

Python Optimal Transport library

pytorch-book

PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)

pytorch-handbook

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

reid-strong-baseline

Bag of Tricks and A Strong Baseline for Deep Person Re-identification

sinkhornautodiff

Toolbox to integrate optimal transport loss functions using automatic differentiation and Sinkhorn's algorithm

soft-dtw

Python implementation of soft-DTW.

svdd

Python code for abnormal detection or fault detection using Support Vector Data Description (SVDD)

wassdistance

Approximating Wasserstein distances with PyTorch

wasserstein-learning-for-point-process

learning point processes by means of optimal transport and wasserstein distance