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38 search results found

Deep universal probabilistic programming with Python and PyTorch

Zhusuan ⭐ 2,139

A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow

Bayesian Neural Networks ⭐ 1,633

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Fortuna ⭐ 824

A Library for Uncertainty Quantification.

Bayesian Torch ⭐ 396

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

Pyvarinf ⭐ 300

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

Bayesflow ⭐ 216

A Python library for amortized Bayesian workflows using generative neural networks.

Pytensor ⭐ 201

PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.

Bayesianrecurrentnn ⭐ 196

Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al

The Books Making You Better ⭐ 169

A list of time-lasting classic books, which not only help you figure out how it works, but also grasp when it works and why it works in that way.

Survival Analysis Using Deep Learning ⭐ 138

This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis

Invertiblenetworks.jl ⭐ 131

A Julia framework for invertible neural networks

Aboleth ⭐ 125

A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

Ml_algo_in_depth ⭐ 124

ML algorithms in depth

Bayesian dessert for Lasagne

Code Repo for "Subspace Inference for Bayesian Deep Learning"

Paper Reading ⭐ 64

Deep Learning over PyTorch

Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors

Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

Cosmopower ⭐ 45

Machine Learning - accelerated Bayesian inference

Artificial_neural_networks ⭐ 35

A collection of Methods and Models for various architectures of Artificial Neural Networks

Quantised Bayesian Nets ⭐ 16

On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks

Bayesian Neural Networks Reading List ⭐ 16

A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesian Deep Learning, by providing an overview of key papers. More details: "A Primer on Bayesian Neural Networks: Review and Debates"

SemI-SUpervised generative Autoencoder models for single cell data

Mathepideeplearning ⭐ 15

Awesome-spatial-temporal-data-mining-packages. Julia and Python resources on spatial and temporal data mining. Mathematical epidemiology as an application. Most about package information. Data Sources Links and Epidemic Repos are also included. Keep updating.

Zhusuan Pytorch ⭐ 14

An Elegant Library for Bayesian Deep Learning in PyTorch

Cosmopower Jax ⭐ 13

Differentiable cosmological emulators: the JAX version of cosmopower

Ursabench ⭐ 12

Codebase for our paper "URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks"

Deep Gaussian Process ⭐ 12

🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0

Robustbnns ⭐ 12

Code for paper "Robustness of Bayesian Neural Networks to Gradient-Based Attacks"

Balanced Nre ⭐ 9

Code for the paper "Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation".

Understanding Bayesian Classification ⭐ 8

On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification

Visual Explanation using Uncertainty based Class Activation Maps

Deep_learning_onboarding ⭐ 8

List of resources for deep learning

Deep Bayesian Self Training ⭐ 7

Deep Bayesian Self-Training [official implementation]

Bayesian Reward Shaping ⭐ 7

Bayesian Reward Shaping Framework for Deep Reinforcement Learning

Some collection of codes that are used in data mining and data science related fields, developed by me

Bayesiandeeplearning ⭐ 6

Overview of Bayesian Deep Learning

Curvature ⭐ 6

Official Code: Estimating Model Uncertainty of Neural Networks in Sparse Information Form, ICML2020.

This is an easy to understand, simplified, broken-down implementation of Diffusion Models written in PyTorch. The architecture is borrowed from the paper "Denoising Diffusion Probabilistic Models"

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1-38 of 38 search results

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