Following along with Statistical Rethinking text on Bayesian modeling by McElreath

Sample scripts of "Machine Learning for Software Engineers"

Jupyter notebooks for sample scripts from 「ITエンジニアのための機械学習理論入門」

Algorithms for inference in Gaussian Mixture Models.

"Probabilistic Machine Learning" - a book series by Kevin Murphy

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Awesome resources on normalizing flows.

PyTorch implementation of normalizing flow models

PyTorch Code used in 'Introduction to Deep Generative Modeling'

Companion webpage to the book "Mathematics For Machine Learning"

[COLM 2024] A Survey on Deep Learning for Theorem Proving

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

My personal notes

Caffe code to accompany my Tutorial on Variational Autoencoders

Simple and clean implementation of Conditional Variational AutoEncoder (CVAE) using PyTorch

This repo implements a simple GAN with fc layers and trains it on MNIST

This repository implements a simpleVAE for training on CPU on the MNIST dataset and provides ability to visualize the latent space, entire manifold as well as visualize how numbers interpolate betw…

This repo implements a Stable Diffusion model in PyTorch with all the essential components.

This repo implements Denoising Diffusion Probabilistic Models (DDPM) in Pytorch

This repo implements ControlNet with DDPM and Latent Diffusion Model in PyTorch with canny edges as conditional control for Mnist and CelebHQ

This repo implements VQVAE on mnist and as well as colored version of mnist images. It also implements simple LSTM for generating sample numbers using the encoder outputs of trained VQVAE

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

Implementation of different diffusion models for probabilistic image generation

Denoising Diffusion Probabilistic Models

Hackable and optimized Transformers building blocks, supporting a composable construction.

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

SCEPTER is an open-source framework used for training, fine-tuning, and inference with generative models.

Inpaint anything using Segment Anything and inpainting models.

Online service using filesystem as backend