hongminwu Goto Github PK

aaltd18

Data augmentation using synthetic data for time series classification with deep residual networks

adaptive_polishing

adversarialnetspapers

The classical paper list with code about generative adversarial nets

ae_ts

Auto encoder for time series

anomaly-detection-resources

Anomaly detection related books, papers, videos and toolboxes

arch

ARCH models in Python

autohmm

Hidden Markov Models (HMMs) with tied states and autoregressive observations

awesome-anomaly-detection

A curated list of awesome anomaly detection resources

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

awesome_time_series_in_python

This curated list contains python packages for time series analysis

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

baxter_data_acquisition

Data acquisition with the Baxter research robot for robot anomaly detection.

betavae_time_series

use the betaVAE model for time series applications

bis

Benchmark on interactive safety

bnpy

The repository is used to compare the Variational Iinference methods of bayesian nonparametric methods.[Python]

bp-ar-hmm

This repository is used to discover and model dynamicl behaviors which are shared among several related time series.

dagmm

My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection

dataset_hongminwu

recorded sensor data from baxter and iiwa robot

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

deepadots

Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

deeplearning-papernotes

Summaries and notes on Deep Learning research papers

disentangled-representation-papers

A curated list of research papers related to learning disentangled representations

disentangled_vae

Replicating "Understanding disentangling in β-VAE"

dmpbbo

C++ library for Function Approximation, Dynamical Movement Primitives, and Black-Box Optimization

dmpling

Dynamic Movement Primitives in Python

dynamic_obstacle_avoidance_cpp

C++ code for the obstacle avoidance

elpy

Emacs Python Development Environment

em

visualizing Expectation Maximization

emacs-python-environment

Python virtualenv API for Emacs Lisp

emacs.d

for saving the configuration of emacs for python developing and .bashrc file