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

A simple and extensible library to create Bayesian Neural Network layers on PyTorch.

PyTorch implementation of bayesian neural network [torchbnn]

PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks

Bayesian neural network using Pyro and PyTorch on MNIST dataset

Recommendation Systems This is a workshop on using Machine Learning and Deep Learning Techniques to build Recommendation Systesm Theory: ML & DL Formulation, Prediction vs. Ranking, Similiarity, Biased vs. Unbiased Paradigms: Content-based, Collaborative filtering, Knowledge-based, Hybrid and Ensembles Data: Tabular, Images, Text (Sequences) Models: (Deep) Matrix Factorisation, Auto-Encoders, Wide & Deep, Rank-Learning, Sequence Modelling Methods: Explicit vs. implicit feedback, User-Item matrix, Embeddings, Convolution, Recurrent, Domain Signals: location, time, context, social, Process: Setup, Encode & Embed, Design, Train & Select, Serve & Scale, Measure, Test & Improve Tools: python-data-stack: numpy, pandas, scikit-learn, keras, spacy, implicit, lightfm Notes & Slides Basics: Deep Learning AI Conference 2019: WhiteBoard Notes | In-Class Notebooks Notebooks Movies - Movielens 01-Acquire 02-Augment 03-Refine 04-Transform 05-Evaluation 06-Model-Baseline 07-Feature-extractor 08-Model-Matrix-Factorization 09-Model-Matrix-Factorization-with-Bias 10-Model-MF-NNMF 11-Model-Deep-Matrix-Factorization 12-Model-Neural-Collaborative-Filtering 13-Model-Implicit-Matrix-Factorization 14-Features-Image 15-Features-NLP Ecommerce - YooChoose 01-Data-Preparation 02-Models News - Hackernews Product - Groceries Python Libraries Deep Recommender Libraries Tensorrec - Built on Tensorflow Spotlight - Built on PyTorch TFranking - Built on TensorFlow (Learning to Rank) Matrix Factorisation Based Libraries Implicit - Implicit Matrix Factorisation QMF - Implicit Matrix Factorisation Lightfm - For Hybrid Recommedations Surprise - Scikit-learn type api for traditional alogrithms Similarity Search Libraries Annoy - Approximate Nearest Neighbour NMSLib - kNN methods FAISS - Similarity search and clustering Learning Resources Reference Slides Deep Learning in RecSys by Balázs Hidasi Lessons from Industry RecSys by Xavier Amatriain Architecting Recommendation Systems by James Kirk Recommendation Systems Overview by Raimon and Basilico Benchmarks MovieLens Benchmarks for Traditional Setup Microsoft Tutorial on Recommendation System at KDD 2019 Algorithms & Approaches Collaborative Filtering for Implicit Feedback Datasets Bayesian Personalised Ranking for Implicit Data Logistic Matrix Factorisation Neural Network Matrix Factorisation Neural Collaborative Filtering Variational Autoencoders for Collaborative Filtering Evaluations Evaluating Recommendation Systems

Bayesian Neural Network in PyTorch

Bayesianize: A Bayesian neural network wrapper in pytorch

Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020

Pytorch implementation of Bayesian physics-informed neural networks

official PyTorch implementation of paper "Continual Meta-Learning with Bayesian Graph Neural Networks" (AAAI2020)

Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch

Migrate to PyTorch. Re-implementation of Bayesian Convolutional Neural Networks (BCNNs)

Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)

[OpenReview] Official PyTorch Implementation for "Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical Variational Inference"

This is a PyTorch implementation of a Bayesian Convolutional Neural Network (BCNN) for Semantic Scene Completion on the SUNCG dataset. Given a depth image the network outputs a semantic segmentation and entropy score in 3D voxel format.

An easy-to-use framework to turn any neural network definition in PyTorch into a Bayesian neural network.

A pytorch module to implement Bayesian neural networks with variational inference

[IJCAI2024] A PyTorch implementation of Full Bayesian Signficance Testing for Neural Networks in Traffic Forecasting

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch

Bayesian Neural Networks in PyTorch

Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch implementation

[AAAI2024] A PyTorch implementation of Full Bayesian Signficance Testing for Neural Networks

PyTorch-native Bayesian neural networks for uncertainty quantification in deep learning

Bayesian Neural Network written in PyTorch with Epistemic and Aleatoric uncertainty estimates captured in weights and biases

A small project for Bayesian Neural network(Pytorch implementation)

pytorch implementation of ICML 17 paper "Dropout inference in Bayesian neural networks with alpha-divergences"

Pytorch implmentation of "V. -C. Luu, J. Park and J. -P. Hong, "Uncertainty-Aware Incremental Automatic Modulation Classification With Bayesian Neural Network," in IEEE Internet of Things Journal, vol. 11, no. 13, pp. 24300-24309, 1 July1, 2024, "

Repo for analysis of bayesian neural networks using pytorch and pyro

PyTorch code for Paper "Uncertainty Estimations by Softplus normalization in Bayesian Convolutional Neural Networks with Variational Inference"