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76 search results found

Bayesian Machine Learning ⭐ 1,587

Notebooks about Bayesian methods for machine learning

Intro_dgm ⭐ 758

An Introduction to Deep Generative Modeling: Examples

Probabilistic_unet ⭐ 400

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

Variational autoencoders for collaborative filtering

Generative_models_tutorial_with_demo ⭐ 268

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..

A pytorch implementation of the vector quantized variational autoencoder (https://arxiv.org/abs/1711.00937)

Deep and Machine Learning for Microscopy

Variational Autoencoder for Dimensionality Reduction of Time-Series

Soft Intro Vae Pytorch ⭐ 157

[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"

Vae Lstm For Anomaly Detection ⭐ 128

We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.

Gumbel-Softmax Variational Autoencoder with Keras

Vae Tensorflow ⭐ 115

A Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).

Normalizing Flows ⭐ 108

Understanding normalizing flows

Deepscm ⭐ 103

Repository for Deep Structural Causal Models for Tractable Counterfactual Inference

Vae Text Generation ⭐ 88

Text Generation Using A Variational Autoencoder

Video_generator ⭐ 63

This is implementation of convolutional variational autoencoder in TensorFlow library and it will be used for video generation.

Music Sketchnet ⭐ 55

ISMIR 2020 Paper repo: Music SketchNet: Controllable Music Generation via Factorized Representations of Pitch and Rhythm

Pytorch_csx ⭐ 54

PyTorch Taipei & NTU CS+X 讀書會

How_to_generate_images_with_tensorflow_live ⭐ 49

Variational Sparse Coding ⭐ 47

Reproducing the paper "Variational Sparse Coding" for the ICLR 2019 Reproducibility Challenge

Vae Pytorch ⭐ 46

AE and VAE Playground in PyTorch

MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations

Vae_protein_function ⭐ 44

Protein function prediction using a variational autoencoder

Conditional_vae ⭐ 37

conditional variational autoencoder written in Keras [not actively maintained]

Flu Sequence Predictor ⭐ 34

An experimental deep learning & genotype network-based system for predicting new influenza protein sequences.

Playing_with_vae ⭐ 34

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

Lossy Vae ⭐ 32

Authors' PyTorch implementation of lossy image compression methods that are based on hierarchical VAEs

Learnedsamplingdistributions ⭐ 29

Vae Latent Space Explorer ⭐ 29

Interactive exploration of MNIST variational autoencoder latent space with React and tensorflow.js.

Cos Cvae ⭐ 29

Diverse Image Captioning with Context-Object Split Latent Spaces (NeurIPS 2020)

Qmldocker ⭐ 28

A docker container for quantum machine learning (QML) research

Flight Delays ⭐ 27

Transfer learning for flight-delay prediction via variational autoencoders in Keras

Sequential Variational Autoencoders for Collaborative Filtering

Ntire22_inpainting ⭐ 24

NTIRE 2022 - Image Inpainting Challenge

Vae In Predicting Stock ⭐ 24

VAE in feature extraction help predicting stock

Minified Generative Models ⭐ 24

Bare-bones implementations of some generative models in Jax: diffusion, normalizing flows, consistency models, flow matching, (beta)-VAEs.

Tensorflow_deep_learning_models ⭐ 23

TensorFlow implementations of several deep learning models (e.g. variational autoencoder, RNN, ...)

Disent And Gen ⭐ 20

Code for the article: The Role of Disentanglement in Generalisation (ICLR, 2021).

This is the code for the paper Embrace the Gap: VAEs perform Independent Mechanism Analysis, showing that optimizing the ELBO is equivalent to optimizing the IMA-regularized log-likelihood under certain assumptions (e.g., small decoder variance).

Molecular Vae ⭐ 19

Pytorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"

Optimisation Python ⭐ 18

A set of notebooks related to convex optimization, variational inference and numerical methods for signal processing, machine learning, deep learning, graph analysis, bayesian programming, statistics or astronomy.

Deep_learning_fmri_eeg ⭐ 18

Implementation of deep learning models in decoding fMRI/EEG data in a context of semantic processing

Variationalautoencoders ⭐ 17

Comparison of Variational Autoencoders with Bayesian Neural Networks. Accuracy, Latent space, Reconstruction and White Noise filtering.

Variational Autoencoder ⭐ 17

PyTorch implementation of Variational Autoencoder (VAE) on MNIST dataset.

SemI-SUpervised generative Autoencoder models for single cell data

Vae_based_segmentation ⭐ 15

Exploring variational-autoencoder-based semantic segmentation for analyzing CT-scans.

Pytorch_vae_cvae ⭐ 15

pytorch implementation Variational Autoencoder and Conditional Variational Autoencoder

Lego Face Vae ⭐ 14

Variational autoencoder for Lego minifig faces

Pytorch Mnist Vae ⭐ 14

Pytorch implementation of GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection

Dirichlet Vae ⭐ 14

Dirichlet-Variational Auto-Encoder by PyTorch

Keras Adversarial Autoencoders ⭐ 13

Experiments with Adversarial Autoencoders using Keras

PyTorch implementation of paper: adVAE: a Self-adversarial Variational Autoencoder with Gaussian Anomaly Prior Knowledge for Anomaly Detection

Generic Expression Patterns ⭐ 11

Distinguishing between generic and experiment-specific gene expression signals.

A probabilistic model to cluster survival data in a variational deep clustering setting

Deep_music ⭐ 9

Recurrent neural network in TensorFlow for generating novel monophonic melodies.

Planar Flow Pytorch ⭐ 9

Pytorch implementation of Planar Flow

Pmr2024 Vae ⭐ 8

An official repository for a VAE tutorial of Probabilistic Modelling and Reasoning (2023/2024) - a University of Edinburgh master's course.

Vae Mxnet ⭐ 8

MXNet/Gluon implementation of the original (Gaussian) Variational Autoencoders (VAE)

Bayesian Methods For Machine Learning ⭐ 8

Bayesian Methods for Machine Learning

Variational_autoencoder_ecg_heartbeat ⭐ 7

Variational Autoencoder for ECG heartbeat dataset

Variational Autoencoder for Molecules

Vae Pytorch ⭐ 7

Implementation of Variational Autoencoder in Pytorch

Accompany Music Vae ⭐ 7

Using Magenta's MusicVAE to generate musical accompaniment.

Variational Autoencoder ⭐ 7

This repository contains code for VAE and CVAE using residual and inverse residual blocks

Generative Models ⭐ 7

Tutorial on deep generative models with experiments on MNIST

Autoencoder Implementations ⭐ 6

This repository contains various Autoencoders implemented using TensorFlow

Amld2020 Workshop ⭐ 6

This repo contains workshop material for Applied Machine Learning Days 2020 conference

Exploratory_data_analysis_and_ml_projects ⭐ 6

Several datasets are manipulated, visualized, and analyzed with well-known ML Algorithms to make predictions, clustering, or classifications.

Image Colorization ⭐ 6

Coloring Black & White Images with the help of Autoencoder, Variational Autoencoder, Generative Adversarial Networks

Tensorflow Advanced Techniques Solutions ⭐ 6

This repository contains my solutions for the Coursera course TensorFlow: Advanced Techniques Specialization. Expand your knowledge of the Functional API and build exotic non-sequential model types. Learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scenarios such as object detection, image segmentation, and interpreting convolutions. Explore generative deep learning including the ways AIs can create new

Colab_tension_vae ⭐ 6

Randomcode ⭐ 6

Rannnnnnnnndoooooooommmmm Code

Generative Deep Learning ⭐ 6

Road towards diffusion models.

Dependency-aware deep generative models for multitasking analysis of spatial genomics data

Generative Models ⭐ 5

Repository for self-teaching of Generative Models and its applications.

Keras Mnist Cvae ⭐ 5

Keras Mnist Vae ⭐ 5

Pytorch Mnist Cvae ⭐ 5

Refinement Of Dl Approaches For Unsupervised Cell Segmentation Classification On Microfluidic Images ⭐ 5

Research internship 2023 at Telecom Paris

Simplydeep ⭐ 5

A simple introduction to deep learning

Vae_workshop ⭐ 5

Code to replicate results from the VAE workshop at ODSC 2018 Kyiv. It's still work in progress

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