variational-autoencoder

Notebooks about Bayesian methods for machine learning

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

Deep probabilistic analysis of single-cell and spatial omics data

"Deep Generative Modeling": Introductory Examples

[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

Open-AI's DALL-E for large scale training in mesh-tensorflow.

A Python package housing a collection of deep-learning multi-modal data fusion method pipelines! From data loading, to training, to evaluation - fusilli's got you covered 🌸

Learn Generative AI with PyTorch (Manning Publications, 2024)

Official implementation of JAMIE, Joint variational Autoencoders for Multimodal Imputation and Embedding

Disentangled Graph Variational Auto-Encoder for Multimodal Recommendation with Interpretability, IEEE TMM