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The Autoencoder contains an encoder and decoder where encoder stores the images input in a compressed form and decoder retrieves back the Images.

Pytorch implementation of a Variational Autoencoder (VAE) that learns from the MNIST dataset and generates images of altered handwritten digits.

This Repository Contains Solution to the Assignments of the Natural Language Processing Specialization from Deeplearning.ai on Coursera Taught by Younes Bensouda Mourri, Łukasz Kaiser, Eddy Shyu

An implementation of Restricted Boltzmann Machine in Pytorch

Animation engine for explanatory math videos

SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

Visualizing CNN filters using PyTorch

A collection of infrastructure and tools for research in neural network interpretability.

DeepVis Toolbox

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

The fastai deep learning library

Predicting galaxy spectra from images

Clean, scalable and easy to use ResNet implementation in Pytorch

Datasets, Transforms and Models specific to Computer Vision

A resource for learning about Machine learning & Deep Learning

Pytorch implementation of convolutional neural network visualization techniques

Basic implementation of ResNet 50, 101, 152 in PyTorch

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

Create simple drawings of neural networks using graphviz

A PyTorch implementation of Adversarial Autoencoders for unsupervised classification

This code uses Wolff algorithm to simulate Potts model, and use phase space to calculate phase-transition temperature

Python, selenium adding advertisement to olx

A guide on STEM PhD admissions