GitHub topics: autoencoders
jeugregg/ocean_protocol_eth_pred
Cryptocurrency AI prediction model
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NathanP23/Introduction-to-Deep-Learning-67822
Exercises from the course "Introduction to Deep Learning (67822)" at The Hebrew University of Jerusalem, in the Department of Computer Science and Engineering.
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xianglin226/Benchmarking-Single-Cell-Perturbation
Single-Cell (Perturbation) Model Library
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Rong-Ding/DecodingUnderPartialObservability
Code and report regarding decoding neural dynamics under partial observabilities using 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.
Language: Python - Size: 10.6 MB - Last synced at: about 3 hours ago - Pushed at: 4 months ago - Stars: 651 - Forks: 98

ashishtripathy2002/Deep-Learning-Assignments-Projects_IIT_Pkd
Deep Learning CourseWork @ IIT Palakkad
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paucablop/chemotools
Integrate your chemometric tools with the scikit-learn API 🧪 🤖
Language: Python - Size: 30.4 MB - Last synced at: 7 days ago - Pushed at: 16 days ago - Stars: 57 - Forks: 7

Qaswara98/Thesis_PCA_vs_AE
This project is a comparative study of Autoencoder (AE) and Principal Component Analysis (PCA) for dimensionality reduction in gene expression data. It aims to understand the unique capabilities and applications of both methods in handling high-dimensional biological data.
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EthanJamesLew/AutoKoopman
AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
Language: Python - Size: 38 MB - Last synced at: 6 days ago - Pushed at: about 1 year ago - Stars: 74 - Forks: 9

alexandru-dinu/cae
Compressive AutoEncoder.
Language: Python - Size: 7.25 MB - Last synced at: 1 day ago - Pushed at: 4 months ago - Stars: 175 - Forks: 32

shyamsn97/barebones-ai
Machine Learning and Deep Learning algorithms built from scratch
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osa-bot/dnaZyme Fork of GenerativeMolMachines/dnaZyme
Predicts DNAzyme catalytic efficiency via LightGBM models & sequence feature engineering, accelerating in silico design and optimization.
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Mehwish39/Predictive-Maintenance-Project
Anomaly detection for predictive maintenance using K-Means, Isolation Forest & Autoencoders. Autoencoder achieved best F1-score (0.91) on 10K+ records, reducing false positives by 35% and enabling real-time failure prediction.
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numaproj/numalogic
Collection of operational time series ML models and tools
Language: Python - Size: 46.3 MB - Last synced at: 22 days ago - Pushed at: 8 months ago - Stars: 171 - Forks: 31

jwcarman/netwerx
A lightweight, extensible deep learning library for Java
Language: Java - Size: 1.83 MB - Last synced at: 26 days ago - Pushed at: 26 days ago - Stars: 2 - Forks: 0

curiousily/Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data
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Devinterview-io/autoencoders-interview-questions
🟣 Autoencoders interview questions and answers to help you prepare for your next machine learning and data science interview in 2025.
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curiousily/Deep-Learning-For-Hackers
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
Language: Jupyter Notebook - Size: 22.2 MB - Last synced at: 30 days ago - Pushed at: about 5 years ago - Stars: 1,048 - Forks: 439

serengil/tensorflow-101
TensorFlow 101: Introduction to Deep Learning
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milaan9/Deep_Learning_Algorithms_from_Scratch
This repository explores the variety of techniques and algorithms commonly used in deep learning and the implementation in MATLAB and PYTHON
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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
Language: Python - Size: 18.8 MB - Last synced at: 26 days ago - Pushed at: over 2 years ago - Stars: 126 - Forks: 17

GiulioTaralli/PyTorch_DeepLearning
This repository contains exercises for learning the PyTorch library and Deep Learning models. Some of these topics were covered during the university course "Neural Networks and Deep Learning", while others were explored independently to deepen expertise in the field.
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HROlive/Applications-of-AI-for-Anomaly-Detection
Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare supervised and unsupervised learning techniques.
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Rohit-Sharma-RS/ML-and-DL
My Machine learning and deep learning projects and templates
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cwkx/GON
Gradient Origin Networks - a new type of generative model that is able to quickly learn a latent representation without an encoder
Language: Python - Size: 2.71 MB - Last synced at: about 1 month ago - Pushed at: over 4 years ago - Stars: 162 - Forks: 20

AR-Version2/Intelligent-SAP-Financial-Integrity-Monitor
Intelligent SAP Financial Integrity Monitor (POC): Hybrid AI/ML (IF, LOF, AE) & rules-based anomaly detection on SAP FAGLFLEXA data using Python/Streamlit
Language: Python - Size: 4.05 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

Tanmoy0077/Credit-Card-Fraud-Detection
Credit Card Fraud Detection using Machine Learning and AutoEncoders
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antonin-lfv/ECG_Generator
ECG generator
Language: Python - Size: 10.2 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

ranimeshehata/Face-Recognition
This project implements a face recognition pipeline using the AT&T Face Dataset (ORL Dataset). It includes dimensionality reduction techniques like PCA, clustering algorithms such as K-Means and GMM, and an optional Autoencoder-based feature extraction.
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GabrieleLozupone/LDAE
Official PyTorch implementation of "Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical Imaging". LDAE is a novel unsupervised framework for 3D medical imaging that combines a latent diffusion model with semantic controls.
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DrAdrianDC/Portfolio-for-Data-Science
This repository contains a collection of end-to-end machine learning and data science projects I have worked on
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Jaguar1225/DL-for-Plasma-Dynamics
Coding team in Nanoscale Processing Laboratory, SKKU
Language: Python - Size: 9.98 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

jbramburger/DataDrivenDynSyst
Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
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oscarhoffmann3487/TDDE70_Deep_Learning
This repository contains my solutions for the TDDE70 Deep Learning course (Linköping University, Spring 2024), including an intro notebook and four labs.
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DREI-8/Autoencoder-Denoising-Diffusion
Image denoising and generation using autoencoders and diffusion models.
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CompVis/net2net
Network-to-Network Translation with Conditional Invertible Neural Networks
Language: Python - Size: 75.2 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 226 - Forks: 21

Josuercuevas/own_repos
Ideas developed or integrated with other publicly available projects
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ChanchalKumarMaji/Fraud-Detection
Fraud Detection
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humanlab/WhiSPA
WhiSPA: Whisper Semantically-Psychologically Aligned with Self-Supervised Contrastive Learning
Language: Python - Size: 4.14 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 6 - Forks: 0

orelz890/CS231n_Assignments_And_Summary
👁️🗨️ Computer Vision Concepts Summary & Assignments 📚🔍
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mohit1106/Fraud-Detection-In-Financial-Transactions
an anomaly detection system on 284,807 transactions, achieving an AUC of ~0.972 with CNNs and Autoencoders.
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petrobras/WPRAutoencoders
This is one of Petrobras' open repositories on GitHub. It contains the WPRAutoencoders project which encompasses a wellbore pressure response generator, a dataset of 20.000 synthetic pressure responses and an autoencoder neural network capable of clustering this data based on transmissibility and reservoir geometry.
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harveyslash/Deep-Steganography
Hiding Images within other images using Deep Learning
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MiaHuebscher/Skin-Cancer-Analysis-and-Detection
applying machine learning tactics (CNNs and anomaly detection) to identify skin cancer from images and patient metadata
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khanhnamle1994/MetaRec
PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models
Language: Python - Size: 626 MB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 303 - Forks: 77

haoliuhl/language-quantized-autoencoders
Language Quantized AutoEncoders
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The-AI-Summer/Introduction-to-Deep-Learning-and-Neural-Networks-Course
Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io
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uni-projects-master/deep-learning-with-pytorch
This repository contains assignments and projects developed during the Deep Learning course.
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Chandrashekar0123/Deep_Learning
This Repository consists of all Deep Learning related projects
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graphixxxx/Denoising_AutoEncoder
This project integrates Autoencoders, PCA, and CNNs for efficient image processing, combining dimensionality reduction, denoising, and enhanced feature extraction for image analysis and compression.
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aqibsaeed/Place-Recognition-using-Autoencoders-and-NN
Place recognition with WiFi fingerprints using Autoencoders and Neural Networks
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ImKeTT/CTG-latentAEs
[Paperlist] Awesome paper list of controllable text generation via latent auto-encoders. Contributions of any kind are welcome.
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Warvito/Normative-modelling-using-deep-autoencoders
Normative modelling using deep autoencoders: a multi-cohort study on mild cognitive impairment and Alzheimer’s disease
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shadoisper/k-sparse-autoencoder
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villacampaporta/synthetic-dielectric-data-gen
🚀 Synthetic Data Generation for Dielectric Characterization using Machine Learning | TVAE & CTGAN for Data Augmentation in Sensor Applications
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TsLu1s/segmentae
SegmentAE: A Python Library for Anomaly Detection Optimization
Language: Python - Size: 111 KB - Last synced at: 2 months ago - Pushed at: 5 months ago - Stars: 7 - Forks: 1

Vinit-source/Deep-Learning-Tasks
Deep Learning assignments performed using PyTorch during MTech at IIT Jodhpur
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arjunravi26/deep_learning
This repo contains codes and notes to learn deep learning
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alexchilton/CAS_AML_Module_3
CAS AML Uni Bern Module 3 covering AutoEncoders, Diffusion Models and some basic tooling
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arjuntheprogrammer/TheSchoolOfAI
Projects for The School of AI
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saurabhdeshpande93/gp-auto-regression
Language: Python - Size: 65.7 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 4 - Forks: 0

kris96tian/MOmics_thesis
COMPARISON OF MULTI-OMICS INTEGRATION METHODS
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AllenInstitute/coupledAE-patchseq
Multimodal data alignment and cell type analysis with coupled autoencoders.
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EPSOFT/Autoencoder
Autoencoder
Language: Jupyter Notebook - Size: 16.6 KB - Last synced at: 4 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

greenelab/DAPS
Denoising Autoencoders for Phenotype Stratification
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12danielLL/Neural_Networks_Project
The project focuses on analyzing neural activity data to classify neuron types (spiny and aspiny). It integrates unsupervised learning methods (PCA, Autoencoders) and supervised learning models (Logistic Regression, MLP) to build accurate classifiers that effectively analyze neurons' electrical responses.
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BenChaliah/Superposition-Transformer
a novel architecture that leverages Autoencoders to superimpose the hidden representations of a base model and a fine-tuned model within a shared parameter space. Using B-spline-based blending coefficients and autoencoders that adaptively reconstruct the original hidden states based on the input data distribution.
Language: Jupyter Notebook - Size: 7.17 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 42 - Forks: 1

Mehrab-Kalantari/Autoencoder-Image-Retrieval
Image retrieval using a simple autoencoder on CIFAR-10 dataset
Language: Jupyter Notebook - Size: 191 KB - Last synced at: 4 months ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

mpatacchiola/Y-AE
Official Tensorflow implementation of the paper "Y-Autoencoders: disentangling latent representations via sequential-encoding", Pattern Recognition Letters (2020)
Language: Python - Size: 13.1 MB - Last synced at: 11 days ago - Pushed at: over 4 years ago - Stars: 52 - Forks: 9

IAmFarrokhnejad/Wine-Quality-Classification
Wine Quality Classification Using Deep Learning
Language: Python - Size: 104 KB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

xnought/introduction-to-autoencoders
Visualize autoencoder model training right in your browser. VISxAI 2021
Language: Svelte - Size: 4.74 MB - Last synced at: 4 months ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

rakibhhridoy/AnomalyDetectionInTimeSeriesData-Keras
Statistics, signal processing, finance, econometrics, manufacturing, networking[disambiguation needed] and data mining, anomaly detection (also outlier detection) is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or errors in a text. Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions.
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mrdvince/autoencoders
Autoencoders are neural networks used for data compression, image de-noising, and dimensionality reduction. Using PyTorch.
Language: Python - Size: 338 KB - Last synced at: 22 days ago - Pushed at: over 4 years ago - Stars: 6 - Forks: 0

codeperfectplus/autoEncoders
Deep convolutional autoencoder for image denoising
Language: PureBasic - Size: 11.1 MB - Last synced at: about 1 month ago - Pushed at: almost 4 years ago - Stars: 8 - Forks: 1

greenelab/adage
Data and code related to the paper "ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa..." Jie Tan, et al · mSystems · 2016
Language: Python - Size: 79.1 MB - Last synced at: about 1 month ago - Pushed at: about 9 years ago - Stars: 61 - Forks: 30

AI-Club-SIT-Pune/Melodify
Exploring Generative Music using Autoencoders
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fazelelham32/DL-Workshop-python-matlab-R-programming
Codes and Project for Deep Learning
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wecarsoniv/augmented-pca
Repository for the AugmentedPCA Python package.
Language: Python - Size: 63 MB - Last synced at: about 1 month ago - Pushed at: 8 months ago - Stars: 10 - Forks: 0

OmarFaig/VAE_vs_GAN
Developed and experimented with linear, convolutional, and variational autoencoder (VAE) and GAN architectures for image generation, analyzing the performance in terms of reconstruction quality and latent space representation
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samuel-adekunle/Autoencoders
Autoencoders Tutorial
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Nishant2018/AutoEncoder-Generative-AI-MNIST
Autoencoders are a type of neural network used for unsupervised learning. In unsupervised learning, the model learns patterns from the data without using labeled outcomes. The goal is to find the underlying structure or representation of the data.
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samresume/ChronoGAN
This advanced framework integrates the benefits of an Autoencoder-generated embedding space with the adversarial training dynamics of GANs for time series generation..
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samresume/SeriesGAN
We introduce an advanced framework that integrates the advantages of an autoencoder-generated embedding space with the adversarial training dynamics of GANs for time series generation.
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christopher-beckham/amr
Official adversarial mixup resynthesis repository
Language: Python - Size: 13.9 MB - Last synced at: 3 months ago - Pushed at: over 5 years ago - Stars: 35 - Forks: 2

AlexDelitzas/fcdae-neural-signal-denoising
Code for the paper "Removing Noise from Extracellular Neural Recordings Using Fully Convolutional Denoising Autoencoders"
Language: Python - Size: 173 MB - Last synced at: 4 months ago - Pushed at: about 3 years ago - Stars: 4 - Forks: 1

tmvadnn/tmva-dnn-tutorial
Notebooks containing examples for different DNN components
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fg-research/lstm-ae-sagemaker
SageMaker implementation of LSTM-AE model for time series anomaly detection.
Language: Jupyter Notebook - Size: 6.11 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 5 - Forks: 0

Anshlulla/Melodify
Exploring Generative Music using Autoencoders
Language: Jupyter Notebook - Size: 1.41 MB - Last synced at: 3 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0

ahmedgh970/adversarial-training
Adversarially Training of Autoencoders for Unsupervised Anomaly Segmentation
Language: Python - Size: 65.4 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 4 - Forks: 0

ahmedgh970/brain-anomaly-seg
Transformer-based Models for Unsupervised Anomaly Segmentation in Brain MR Images
Language: Python - Size: 120 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 20 - Forks: 3

hauntedcupoftea/vaani Fork of 7Zenox/vaani
A religion based question answering AI, developed in collaboration for a university course on Design, Thinking and Innovation as part of my bachelor's degree.
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OleksiiLatypov/Practical-Deep-Learning-with-PyTorch
DataRoot Labs Practical Deep Learning with PyTorch
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PetropoulakisPanagiotis/igae
State Representations as Incentives for Reinforcement Learning Agents: A Sim2Real Analysis on Robotic Grasping
Language: Python - Size: 45.3 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

bvpsk/Variational-Auto-Encoder-VAE-
Implementing VAE in keras and training on CelebA dataset
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TristanThorn/uwaterloo-skin-cancer-segmentation
An initial phase segmentation using LinkNet on the skin lesion dataset managed by VISION AND IMAGE PROCESSING LAB, University of Waterloo. Public dataset on Kaggle at https://www.kaggle.com/datasets/mahmudulhasantasin/university-of-waterloo-skin-cancer-db-80-10-10/.
Language: Python - Size: 94.7 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

animikhaich/Semantic-Segmentation-using-AutoEncoders
Lightweight and Fast Person Segmentation using Autoencoders (Trained Weights Included)
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webstah/self-supervised-bss-via-multi-encoder-ae
Official repository for "Blind Source Separation of Single-Channel Mixtures via Multi-Encoder Autoencoders".
Language: Jupyter Notebook - Size: 8.02 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 14 - Forks: 3

jaiminjariwala/pytorch_concepts
From basic pytorch concepts to autoencoders, cnn's, data-augmentation, etc.
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ndrplz/transforming-autoencoders
Transforming Autoencoder (Hinton et al.) implementation in TensorFlow. A way to get hands dirty with Hinton's capsules.
Language: Python - Size: 21.3 MB - Last synced at: 3 months ago - Pushed at: over 7 years ago - Stars: 29 - Forks: 9

nonlocal/autoencoder_example
Language: Jupyter Notebook - Size: 3.91 KB - Last synced at: 11 months ago - Pushed at: over 8 years ago - Stars: 0 - Forks: 0
