Unofficial implementation of SVMs multi-class loss feedback based discriminative dictionary learning in python

Building Auto-encoders using Deep Learning models in PyTorch

An image-based deep learning model to help predict the the occurrence of a stampede

Uniform Vectorized AutoEncoder : latent vectors distribution is attacked by adversarial model

Collaborative Filtering With User or Item Feature

Delved into advanced techniques to enhance ML performance during the uOttawa 2023 ML course. This repository offers Python implementations of Naïve Bayes (NB) and K-Nearest Neighbor (KNN) classifiers on the MCS dataset.

This model implements auto-encoder for speech data using deep convolution neural networks in pytorch

Basic autoencoder for the mnist-dataset

Research on Material Science using Neural Networks black box approach

2020.06 개인프로젝트 원숭이 이미지 분류

This repository if for creating auto-encoders easily. The main focus of the auto-encoders on this page is for genetic and spectral data analysis but likely could be used for any high dimensional data

Deep generative models especially Auto Encoders and VAEs in both TensorFlow and PyTorch.

EE456 final project exploring the Auto Encoder CNN architecture in 2022.

Clustering with feature extracted from auto encoder gives better result than K-Means.

This is the Web-server code for SAXS_reconstruction programs

clone of gitlab

Image Denoising with Auto-Encoder

Boltzmann Machine and Self Organizing Maps are implemented in this repository

Code and Datasets for the paper "Identifying Sepsis Subphenotypes via Time-Aware Multi-ModalAuto-Encoder", published on KDD 2020.