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aaltd18

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

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

autoseries

awesome-anomaly-detection

A curated list of awesome anomaly detection resources

awesome-community-detection

A curated list of community detection research papers with implementations.

awesome-fraud-detection-papers

A curated list of data mining papers about fraud detection.

awesome-ts-anomaly-detection

List of tools & datasets for anomaly detection on time-series data.

awesome_time_series_in_python

This curated list contains python packages for time series analysis

bigdata18

Transfer learning for time series classification

brits

Code of NIPS18 Paper: BRITS: Bidirectional Recurrent Imputation for Time Series

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

deeptables

DeepTables: Deep-learning Toolkit for Tabular data

deeptraffic

Deep Learning models for network traffic classification

dl-4-tsc

Deep Learning for Time Series Classification

educdm

The Model Zoo of Cognitive Diagnosis Models, including classic Item Response Ranking (IRT), Multidimensional Item Response Ranking (MIRT), Deterministic Input, Noisy "And" model(DINA), and advanced Fuzzy Cognitive Diagnosis Framework (FuzzyCDF), Neural Cognitive Diagnosis Model (NCDM) and Item Response Ranking framework (IRR).

fancyimpute

Multivariate imputation and matrix completion algorithms implemented in Python

fost

FOST is a general forecasting tool, which demonstrate our experience and advanced technology in practical forecasting domains, including temporal, spatial-temporal and hierarchical forecasting. Current general forecasting tools (Gluon-TS by amazon, Prophet by facebook etc.) can not process and model structural graph data, especially in spatial domains, also those tools suffer from tradeoff between usability and accuracy. To address these challenges, we design and develop FOST and aims to empower engineers and data scientists to build high-accuracy and easy-usability forecasting tools.

g-mlp-pytorch

Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch

github-slideshow

A robot powered training repository :robot:

gru-d

Gated Recurrent Unit with a Decay mechanism for Multivariate Time Series with Missing Values

helloworld

ijcnn19ensemble

Deep Neural Network Ensembles for Time Series Classification

list-of-papers

Curated List of papers on Time Series Analysis

lstm_encoder_decoder

Build a LSTM encoder-decoder using PyTorch to make sequence-to-sequence prediction for time series data

maro

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

mlstm-fcn

Multivariate LSTM Fully Convolutional Networks for Time Series Classification

mtgnn

multi-nilm

Multi-NILM: Multi Label Non Intrusive Load Monitoring

paddle

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

pdfs

Technically-oriented PDF Collection (Papers, Specs, Decks, Manuals, etc)