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autoencoders

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AutoViML / featurewiz

Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.

feature-selection feature-extraction xgboost feature-engineering autoencoders categorical-variables mrmr rfe featuretools rfecv feature-encoding best-encoders feature-engg

Updated Feb 19, 2025
Python

MetaRec

khanhnamle1994 / MetaRec

PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models

django deep-learning tensorflow pytorch collaborative-filtering matrix-factorization ranking tensorboard boltzmann-machines recommender-systems autoencoders movielens-dataset meta-learning multilayer-perceptron cometml wandb

Updated Nov 21, 2022
Python

vuptran / graph-representation-learning

[DSAA 2018] Autoencoders for Link Prediction and Semi-Supervised Node Classification

deep-learning semi-supervised-learning autoencoders network-embedding link-prediction graph-representation node-classification

Updated Jul 18, 2019
Python

CompVis / net2net

Network-to-Network Translation with Conditional Invertible Neural Networks

lightning pytorch generative-model inn gans autoencoders normalizing-flows pytorch-lightning streamlit

Updated Dec 20, 2022
Python

pcko1 / Deep-Drug-Coder

A tensorflow.keras generative neural network for de novo drug design, first-authored in Nature Machine Intelligence while working at AstraZeneca.

neural-network drug-discovery molecules autoencoders lstm-neural-networks denovo-design smiles-strings

Updated Mar 24, 2023
Python

alexandru-dinu / cae

Compressive AutoEncoder.

autoencoders binarization lossy-image-compression

Updated Feb 25, 2025
Python

numaproj / numalogic

Collection of operational time series ML models and tools

python machine-learning deep-learning time-series outlier-detection unsupervised-learning autoencoders hacktoberfest variational-autoencoder

Updated Oct 15, 2024
Python

FutureXiang / ddae

[ICCV 2023 Oral] Official Implementation of "Denoising Diffusion Autoencoders are Unified Self-supervised Learners"

classification autoencoders diffusion generative-models self-supervised-learning diffusion-models

Updated Feb 19, 2024
Python

cwkx / GON

Gradient Origin Networks - a new type of generative model that is able to quickly learn a latent representation without an encoder

machine-learning neural-networks networks implicit representation siren unsupervised-learning autoencoders generative-models

Updated Feb 4, 2021
Python

nmichlo / disent

🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervised, weakly supervised and unsupervised methods ▸ Easily configured and run with Hydra config ▸ Inspired by disentanglement_lib

python metrics python3 pytorch vae metric-learning datasets representation-learning configurable autoencoders disentanglement disentangled-representations pytorch-lightning

Updated Mar 21, 2023
Python

yinboc / dito

Official PyTorch Implementation of "Diffusion Autoencoders are Scalable Image Tokenizers"

autoencoders diffusion-models

Updated Jan 31, 2025
Python

dr-costas / mad-twinnet

The code for the MaD TwinNet. Demo page:

audio deep-neural-networks deep-learning voice pytorch recurrent-neural-networks wav music-information-retrieval deeplearning autoencoders audio-signal-processing denoising-autoencoders audio-processing source-separation music-signal-processing music-source-separation twin-networks singing-voice mad-twinnet

Updated Feb 15, 2023
Python

haoliuhl / language-quantized-autoencoders

Language Quantized AutoEncoders

autoencoders bert vq multimodal roberta vqvae large-language-models

Updated Feb 7, 2023
Python

vmicheli / delta-iris

Efficient World Models with Context-Aware Tokenization. ICML 2024

machine-learning research reinforcement-learning deep-learning transformers autoencoders world-models artificial-inteligence

Updated Sep 22, 2024
Python

EthanJamesLew / AutoKoopman

AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.

deep-learning reachability dynamical-systems autoencoders system-identification sindy dynamic-mode-decomposition koopman koopman-operators data-driven-dynamics

Updated May 7, 2024
Python

hamaadshah / autoencoders_tensorflow

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

python machine-learning deep-learning tensorflow keras feature-extraction autoencoder bayesian-inference representation-learning feature-engineering autoencoders

Updated Feb 15, 2023
Python

xianglin226 / Benchmarking-Single-Cell-Perturbation

Single-Cell (Perturbation) Model Library

drug-discovery drug-repurposing drug single-cell autoencoders disentanglement perturbations counterfactual-inference llm

Updated Jun 24, 2025
Python

ReyhaneAskari / pytorch_experiments

Auto Encoders in PyTorch

pytorch autoencoders denoising-autoencoders variational-autoencoder pytorch-tutorial autoencoder-mnist

Updated Jan 29, 2018
Python

57AE

greenelab / adage

Data and code related to the paper "ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa..." Jie Tan, et al · mSystems · 2016

data machine-learning research paper gene-expression dataset neural-networks methodology manuscript autoencoders denoising-autoencoders pseudomonas-aeruginosa supplement

Updated May 26, 2016
Python

nikhil-dce / Transforming-Autoencoder-TF

Tensorflow implementation of "Transforming Autoencoders" (Proposed by G.E.Hinton, et al.)

machine-learning deep-learning tensorflow representation-learning autoencoders transforming-autoencoders transformation-learning

Updated Oct 5, 2017
Python

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