179 Open source projects that are alternatives of or similar to sldm4-h2o

Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders

Tensorflow Implementation of Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation (NAACL 2019).

Interactive Visual Machine Learning Demos.

Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)

Tensorflow implementation of adversarial auto-encoder for MNIST

Colorizing B&W Photos with Neural Networks

Dual CNN Models for Unsupervised Monocular Depth Estimation

AE and VAE Playground in PyTorch

Hands-on in-person workshop for Deep Learning with TensorFlow

Neural network library written in C and Javascript

Autoencoder trained on ImageNet Using Torch 7

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

Global NIPS Paper Implementation Challenge of "Hiding Images in Plain Sight: Deep Steganography"

SESF-Fuse: An Unsupervised Deep Model for Multi-Focus Image Fusion

Experiments with Adversarial Autoencoders using Keras

Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.

JCLAL is a general purpose framework developed in Java for Active Learning.

NOTE: skutil is now deprecated. See its sister project: https://github.com/tgsmith61591/skoot. Original description: A set of scikit-learn and h2o extension classes (as well as caret classes for python). See more here: https://tgsmith61591.github.io/skutil

Implementations of autoencoder, generative adversarial networks, variational autoencoder and adversarial variational autoencoder

Real time face landmarking using decision trees and NN autoencoders

Noise removal from images using Convolutional autoencoder

JuliaLang version of "An Introduction to Statistical Learning: With Applications in R"

eForest: Reversible mapping between high-dimensional data and path rule identifiers using trees embedding

Easy Reduced Basis method

A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners

Showcase for using H2O and R for churn prediction (inspired by ZhouFang928 examples)

A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python

Shared Latent Space VAE's

Convolutional AutoEncoder application on MRI images

No description or website provided.

Mercury-ML is an open source Machine Learning workflow management library. Its core contributors are employees of Alexander Thamm GmbH

Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.

A new approach to video compression by refining the shortcomings of conventional approach and substituting each traditional component with their neural network counterpart. Our proposed work consists of motion estimation, compression and compensation and residue compression, learned end-to-end to minimize the rate-distortion trade off. The whole…

It is a blueprint to data science from the mathematics to algorithms. It is not completed.

Deep learning image autoencoder that not depends on image resolution

This is my attempt to reproduce and extend the results in the paper "An Introduction to Deep Learning for the Physical Layer" by Tim O'Shea and Jakob Hoydis

Lecture Slides for Introduction to Data Science

Learning about Haskell with Variational Autoencoders

The implementation of "Gated Attentive-Autoencoder for Content-Aware Recommendation"

Advanced Normalization Tools in R

Matlab library for gradient descent algorithms: Version 1.0.1

📈 Machine Learning from the perspective of a Statistician using R

Unsupervised (Self-Supervised) Clustering of Seismic Signals Using Deep Convolutional Autoencoders

BoostSRL: "Boosting for Statistical Relational Learning." A gradient-boosting based approach for learning different types of SRL models.

Exemplary, annotated machine learning pipeline for any tabular data problem.

基于Julia 1.0写李航博士《统计学习方法》

Identifying diseases in chest X-rays using convolutional neural networks

Univariate and multivariate time series forecasting

Image retrieval program made in Tensorflow supporting VGG16, VGG19, InceptionV3 and InceptionV4 pretrained networks and own trained Convolutional autoencoder.

📈 PyTorch dual-attention LSTM-autoencoder for multivariate Time Series 📈

This is the official implementation for the paper 'AutoEncoder by Forest'

Multi-omics Autoencoder Integration: Deep learning-based heterogenous data analysis toolkit

Tensorflow 2.0 implementation of Adversarial Autoencoders

Python binding for the H2O HTTP server

Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression"

Variational autoencoder, denoising autoencoder and other variations of autoencoders implementation in keras

PyTorch implementation of 'An Unsupervised Neural Attention Model for Aspect Extraction' by He et al. ACL2017'

DEPRECATED Build, manage and deploy H2O's high-speed machine learning models.

This is the official implementation for IVA '19 paper "Analyzing Input and Output Representations for Speech-Driven Gesture Generation".

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.