828 Open source projects that are alternatives of or similar to DeepEcho

MTSS-GAN: Multivariate Time Series Simulation with Generative Adversarial Networks (by @firmai)

Synthetic Data Generation for tabular, relational and time series data.

Genalog is an open source, cross-platform python package allowing generation of synthetic document images with custom degradations and text alignment capabilities.

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

GRATIS: GeneRAting TIme Series with diverse and controllable characteristics

[IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions

The Declarative Data Generator

Benchmarking synthetic data generation methods.

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

Conditional GAN for generating synthetic tabular data.

List of useful data augmentation resources. You will find here some not common techniques, libraries, links to github repos, papers and others.

This repository is a non-official implementation of TimeGAN (Yoon et al., NIPS2019) using PyTorch.

GANs for time series generation in pytorch

This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.

A Java library for Matrix Profile

Bayesian Generalized Linear Models with Time-Varying Coefficients

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

Code examples for pyFTS

Scalable machine 🤖 learning for time series forecasting.

Tensorflow Implementation of DiscoGAN

Renewcast: Forecasting Renewable Electricity Generation in EU Countries.

🐳 GAN implemented as Tensorflow 2.X

My pytorch implementation for GAN

Pure tensorflow implementation of progressive growing of GANs

Rainfall analysis of Maharashtra - Season/Month wise forecasting. Different methods have been used. The main goal of this project is to increase the performance of forecasted results during rainy seasons.

Process global-scale satellite and airborne elevation data into time series of glacier mass change: Hugonnet et al. (2021).

Dynamic Time Warping in Python / C (using ctypes)

Historical NAV/price/time-series data of mutual funds and popular benchmark indices in India

Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.

Automatic feature engineering using Generative Adversarial Networks using Deeplearning4j and Apache Spark.

This is the official GitHub repository for ECCV 2020 Workshop paper "Single image dehazing for a variety of haze scenarios using back projected pyramid network"

Given a simple anime line-art sketch the model outputs a decent colored anime image using Conditional-Generative Adversarial Networks (C-GANs) concept.

Out-of-Distribution Detection for Generalized Zero-Shot Action Recognition

Dataset and Code for our CVPR'18 paper ST-CGAN: "Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal"

Tensorflow-based framework to ease training of generative models

Official Implementation for "HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing" (CVPR 2022) https://arxiv.org/abs/2111.15666

Creating a model to analyze and predict the trend of the prices of gold.

Path Planning using Generative Adversarial Network (GAN)

Statistical inference on machine learning or general non-parametric models

Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io

Generate arbitrary queries matching your GraphQL schema, and use them to verify your backend implementation.

Official code (Pytorch) for paper Perception-Enhanced Single Image Super-Resolution via Relativistic Generative Networks

The Gretel Python Client allows you to interact with the Gretel REST API.

Tensorflow implementation of paper "unsupervised image to image translation networks"

An overview of univariate time series forecasting models with sample code.

3D-aware GANs based on NeRF (arXiv).

Python package for early warning signals (EWS) of bifurcations in time series data.

Code for “Convolutional Generative Adversarial Networks with Binary Neurons for Polyphonic Music Generation”

No description or website provided.

Reusable CNN and RNN model doing time series binary classification

Forecast time series and stock prices with SCINet

sknifedatar is a package that serves primarily as an extension to the modeltime 📦 ecosystem. In addition to some functionalities of spatial data and visualization.

An OpenTSDB-like time series database, with much better performance.

LSTM Mobility Model implementation using Tensorflow

Using LSTM network for time series forecasting

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

Example of order book modeling.

PyTorch study

Library and CLI for randomly generating medical data like you might get out of an Electronic Health Records (EHR) system

A Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"