sienna13's repositories
2015-SIGGRAPH-convolutional-ot
J. Solomon, F. de Goes, G. Peyré, M. Cuturi, A. Butscher, A. Nguyen, T. Du, L. Guibas. Convolutional Wasserstein Distances: Efficient Optimal Transportation on Geometric Domains. ACM Transactions on Graphics (Proc. SIGGRAPH 2015), 34(4), pp. 66:1–66:11, 2015
2016-ICML-gromov-wasserstein
Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.
cvae
Conditional variational autoencoder implementation in Torch
dcgan_vae_pytorch
dcgan combined with vae in pytorch!
DNGR
Source Code of DNGR
EEGrunt
A Collection Python EEG (+ ECG) Analysis Utilities for OpenBCI and Muse
Enigma
Multiplatform payload dropper
graph-generation
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
GraphGAN
A tensorflow implementation of GraphGAN (Graph Representation Learning with Generative Adversarial Nets)
Machine-Learning-Models
Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means
MidiNet
This repository contains the source code of MdidNet : A Convolutional Generative Adversarial Network for Symbolic-domain Music Generation
Pitch-Tracking
Pitch detection algorithms in Matlab
pyda-2e-zh
:book: [译] 利用 Python 进行数据分析 · 第 2 版
pytorch-generative-adversarial-networks
A very simple generative adversarial network (GAN) in PyTorch
S-WMD
Code for Supervised Word Mover's Distance (SWMD)
SciPy2015
Talk for SciPy2015 "Deep Learning: Tips From The Road"
VAE-GAN-Pytorch
Generation of 128x128 bird images using VAE-GAN with additional feature matching loss
vae_tutorial
Caffe code to accompany my Tutorial on Variational Autoencoders
wasserstein-dist
tensorflow implementation of the Wasserstein (aka optimal transport) distance
Wasserstein-Learning-For-Point-Process
learning point processes by means of optimal transport and wasserstein distance
wasserstein-notebook
Wasserstein / earth mover's distance visualizations