tensorflow-probability

ksachdeva/rethinking-tensorflow-probability

Statistical Rethinking (2nd Ed) with Tensorflow Probability

mohd-faizy/Probabilistic-Deep-Learning-with-TensorFlow

Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real-world datasets.

uPeppe/fantabeto

Machine learning model for predicting Serie A players performance in a match, in terms of Fantacalcio (italian fantasy football) scores.

zhulingchen/tfp-tutorial

TensorFlow Probability Tutorial

a-ws-m/unlockNN

A Python package for adding uncertainties to neural network models of chemical systems.

Frightera/Medium_Notebooks_English

This repo contains the notebooks that is used in Medium posts.

KarenUllrich/binary-VAE

A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.

aaryapatel007/Patient-Selection-for-Diabetes-Drug-Testing

Built a regression model that predicts the expected days of hospitalization time and an uncertainty range estimation.

MArpogaus/bernstein_flow

A normalizing flow using Bernstein polynomials for conditional density estimation.

csamuelsson/bayesianNN

Implementing a bayesian neural network in TensorFlow

Himscipy/bnn_hvd

Distributed Training of Bayesian Neural Networks at Scale

fomorians-oss/pyoneer

Tensor utilities, reinforcement learning, and more!

siddhantpathakk/tensorflow-ml

TensorFlow ML - an abstract implementation of commonly used machine learning algorithms using TensorFlow. Feel free to contribute! (Work in Progress)

Ellie190/BCNN-for-Ocular-Disease-Classification

A Bayesian Convolutional Neural Network model for classifying Cataract in Ocular Disease with measurements of uncertainty

kristpapadopoulos/categorical-variational-autoencoder

Keras, Tensorflow eager execution implementation of Categorical Variational Autoencoder

kristpapadopoulos/neural-processes

Keras, Tensorflow eager execution implementation of Neural Processes

itsayushthada/Probabislitc-Deep-Learning

Exploration of TensorFlow-2 and TensorFlow probability to implement Bayesian Neural Networks, Normalizing flows, real NVPs and Autoencoders. Exploration of Bayesian Modelling and Variational Inference with Pyro.

yoonholee/edward2-notebooks

Jupyter Notebooks that show the basic functionalities of edward2

tr7200/CBNN_SEM_loss_convergence

Code accompanying my 2021 ASA SDSS paper

aliizadi/probabilistic-programming-workshop

All codes and contents provided for the probabilistic programming workshop in Amirkabir Artificial Intelligence Student Summit (2021)

jetnew/Simkit

A generalized framework for generative and probabilistic modelling for training reinforcement learning agents in TensorFlow 2.

akensert/reinforceable

Deep reinforcement learning implementations with TensorFlow and TensorFlow probability.

SamArgt/AudioSourceSep

Statistics MSc Project (2020): Audio Source Separation

slowmoyang/BayesianDeepLearning

abhimanyu911/bayesian_sdss

A Bayesian CNN approach to SDSS image data classification

danftang/MutableCategoricalDistribution

A categorical distribution with efficient sampling and modification of category probabilities

JBris/sbi-epidemiology

Simulation based inference for epidemiology

jilljenn/vae

Variational Factorization Machines in TensorFlow and PyTorch

Luca96/reinforce-lib

Reinforce-lib is a easy to use, simple to extend reinforcement learning library for Python: https://pos.sissa.it/415/018/pdf.

nicenustian/bh2igm

This code finds an optimal architecture, search for hyperparameters (using OPTUNA code), trains and make predictions using LYMAN alpha part of simulated 1D super massive black hole spectra and converts it to intergalactic medium gas conditions along the line of sight. However, this code easily be utilized for ANY 1D signals using supervised ML.

OpenSUTD/ProbStats-with-TFP

Prob&Stats with TensorFlow Probability

slowmoyang/bayesian-deep-learning

suriyadeepan/PracticalBayes

Probabilistic programming, Bayesian Thinking, Bayesian Data Analysis and Applications

TheUnsolvedDev/ProbabilisticMadness

Statistics and Machine Learning in depth analysis with Tensorflow Probability

wataruhashimoto52/nmf_tfp

Implementation of Bayesian Non-negative Matrix Factorization using Variational Inference with TensorFlow Probability