2419 Open source projects that are alternatives of or similar to Ad_examples

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation

[CVPR 2020] Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation

The Simplest DCGAN Implementation

Discovering Interpretable GAN Controls [NeurIPS 2020]

Handwritten Chinese Characters Generation

Implementation of Apple's Learning from Simulated and Unsupervised Images through Adversarial Training

Machine Learning and having it Deep and Structured (MLDS) in 2018 spring

Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.

RNN(SimpleRNN, LSTM, GRU) Tensorflow2.0 & Keras Notebooks (Workshop materials)

rnn trained on r/totallynotrobots 🤖

GAN Playground - Experiment with Generative Adversarial Nets in your browser. An introduction to GANs.

Official Implementation of the paper "A U-Net Based Discriminator for Generative Adversarial Networks" (CVPR 2020)

Semantic Image Inpainting

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

🎎 InfoGAN: Interpretable Representation Learning

Lightweight C++11 library for building deep recurrent neural networks

Pull stock prices from online API and perform predictions using Long Short Term Memory (LSTM) with TensorFlow.js framework

Keras implementation of 3D Generative Adversarial Network.

An extremely simple generative adversarial network, built with TensorFlow

Anomaly detection implemented in Keras

DCGAN image generator 🖼️.

GANnotation (PyTorch): Landmark-guided face to face synthesis using GANs (And a triple consistency loss!)

Tensorflow implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Netwokrs for MNIST dataset.

Collection of generative models in Pytorch version.

A stable algorithm for GAN training

Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/

Video lstm auto encoder built with pytorch. https://arxiv.org/pdf/1502.04681.pdf

Deep Learning Super Sampling with Deep Convolutional Generative Adversarial Networks.

ICCV 2019 (oral) RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution. PyTorch implementation

ArtGAN: This work presents a series of new approaches to improve Generative Adversarial Network (GAN) for conditional image synthesis and we name the proposed model as “ArtGAN”. Implementations are in Caffe/Tensorflow.

Everything about Generative Adversarial Networks

The Implementation of paper "Controllable Person Image Synthesis with Attribute-Decomposed GAN"

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.

TensorFlow 1.3 experiment with LSTM (and GRU) RNNs for sine prediction

This is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.

Part-of-Speech Tagger and custom implementations of LSTM, GRU and Vanilla RNN

🌊 Numerically solving and backpropagating through the wave equation

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

Unsupervised Anomaly Detection with Generative Adversarial Networks on MIAS dataset

Hybrid Code Networks https://arxiv.org/abs/1702.03274

Tensorflow implementation of Synthetic Gradient for RNN (LSTM)

Solution to Kaggle - Web Traffic Time Series Forecasting

Durable time-series database that's API-compatible with Prometheus.

Timeseries database

A stock trading bot that uses machine learning to make price predictions.

Luminaire is a python package that provides ML driven solutions for monitoring time series data.

Anything can happen in the next half hour (including spectral timing made easy)!

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

Bringing financial analysis to the tidyverse

Long short-term memory recurrent neural networks for learning peptide and protein sequences to later design new, similar examples.

使用Theano实现的一些RNN代码，包括最基本的RNN，LSTM，以及部分Attention模型，如论文MLSTM等

MotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and gyroscope)

PyTorch reimplementation of the paper: "Semantic Pyramid for Image Generation" [CVPR 2020].

Generate Cartoon Images using Generative Adversarial Network

High-performance time series algorithms for Ruby

Thio - a playground for real-time anomaly detection

[TIP2020] Pytorch implementation of "Towards Unsupervised Deep Image Enhancement with Generative Adversarial Network"