tensorflow-probability

There are 1 repository under tensorflow-probability topic.

• WillianFuks / tfcausalimpact

  Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.

  causalimpacttensorflow-probabilitypythoncausal-inference
  Language:Python 574

• ksachdeva / rethinking-tensorflow-probability

  Statistical Rethinking (2nd Ed) with Tensorflow Probability

  bayesian-inferencebayesian-statisticsmarkov-chain-monte-carlostatistical-rethinkingtensorflowtensorflow-probabilitytutorialsvariational-inference
  Language:Jupyter Notebook 269

• 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.

  tensorflow-probabilityprobabilistic-deep-learningdeep-probabilistic-modelsprobabilistic-layerstensorflow2kerasprobabilistic-programmingpoisson-distributionbernoulli-distributionbinomial-distributionsunivariate-distributionstfpmachine-learningmultivariate-distributionstensorflow
  Language:Jupyter Notebook 56

• zhulingchen / tfp-tutorial

  TensorFlow Probability Tutorial

  deep-learningdeep-neural-networksresnettensorflow-probabilitykeras
  Language:Jupyter Notebook 35

• uPeppe / fantabeto

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

  aifantacalciofantasy-footballmachine-learningneural-networkpythonserie-atensorflowtensorflow-probability
  Language:Jupyter Notebook 29

• Frightera / Medium_Notebooks_English

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

  tensorflowkerastensorflow-probabilitybayesian-deep-learning
  Language:Jupyter Notebook 23

• a-ws-m / unlockNN

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

  pythonmachine-learningkerasmaterials-sciencechemistrytensorflow-probability
  Language:PureBasic 21

• KarenUllrich / binary-VAE

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

  tensorflowtensorflow-probabilityvaevariational-autoencodervariational-inferenceconcrete-distributionbernoullibinarytensorflow-eager
  Language:Python 19

• MArpogaus / TensorFlow-Probability-Bernstein-Polynomial-Bijector

  A normalizing flow using Bernstein polynomials for conditional density estimation.

  tensorflow-probabilitybernstein-polynomialsmachine-learningprobabilistic-modelingtensorflow2regression
  Language:Jupyter Notebook 14

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

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

  tensorflowregressiontensorflow-probabilityai-for-healthcareehr-datauncertainty-estimationfeature-engineering
  Language:Jupyter Notebook 11

• csamuelsson / bayesianNN

  Implementing a bayesian neural network in TensorFlow

  tensorflowtensorflow-probabilitybayesian-neural-networksvariational-inference
  Language:Python 11

• Himscipy / bnn_hvd

  Distributed Training of Bayesian Neural Networks at Scale

  bayesian-networkshorovodmachine-learningcomputer-visiondistributed-computingmnisttensorflowtensorflow-probabilityuncertainty-quantificationvariational-inferencedata-science
  Language:Python 11

• fomorians-oss / pyoneer

  Tensor utilities, reinforcement learning, and more!

  tensorflowmachine-learningreinforcement-learningeager-executiondeep-learninggymtensorflow-probability
  Language:Python 9

• siddhantpathakk / tensorflow-ml

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

  kerasmachine-learning-algorithmsnumpytensorflow-decision-foreststensorflow-probabilitytensorflow2
  Language:Python 8

• Ellie190 / BCNN-for-Ocular-Disease-Classification

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

  bayesian-methodsbayesian-probabilistic-modelsclassificationconvolutional-neural-networksimage-classificationkerasmachine-learningopencvprobabilistic-machine-learningtensorflowtensorflow-probabilityuncertainty-quantificationuncertainty-visualisation
  Language:Jupyter Notebook 6

• kristpapadopoulos / categorical-variational-autoencoder

  Keras, Tensorflow eager execution implementation of Categorical Variational Autoencoder

  variational-autoencodermnistcategorical-variational-autoencodergumbel-softmaxcategoricalgenerative-modeltensorflow-probabilitykerastensorflow-eagertorontokrist-papadopoulostensorflowvariational-inference
  Language:Python 6

• kristpapadopoulos / neural-processes

  Keras, Tensorflow eager execution implementation of Neural Processes

  neural-processesvariational-inferenceneural-networktensorflowtensorflow-probabilitykerasregressiontorontokrist-papadopoulosvariational-autoencodertime-series
  Language:Python 6

• yoonholee / edward2-notebooks

  Jupyter Notebooks that show the basic functionalities of edward2

  jupyter-notebooktensorflow-tutorialstensorflow-notebookstensorflow-probabilityedward2
  Language:Jupyter Notebook 6

• tr7200 / CBNN_SEM_loss_convergence

  Code accompanying my 2021 ASA SDSS paper

  causal-inferencecausalitycausal-modelscausality-analysiscausal-networksneural-networkneural-networksdirected-acyclic-graphstructural-equation-modelingmerchandisingtensorflow-probability
  Language:Python 5

• aliizadi / probabilistic-programming-workshop

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

  probabilistic-programmingprobabilistic-graphical-modelsbayesian-statisticstensorflow-probabilitypymc3
  Language:Jupyter Notebook 4

• 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.

  bayesian-inferencebayesian-machine-learningbayesian-neural-networksdeep-learningprobabilistic-deep-learningprobabilistic-modellingpyrotensorflow-2tensorflow-probabilityvariational-inference
  Language:Jupyter Notebook 4

• jetnew / Simkit

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

  reinforcement-learningmachine-learningneural-networksprobabilistic-modelsbayesian-statisticstensorflowtensorflow-probability
  Language:Jupyter Notebook 4

• SamArgt / AudioSourceSep

  Statistics MSc Project (2020): Audio Source Separation

  source-separationnormalizing-flowstensorflow-probability
  Language:Python 4

• slowmoyang / BayesianDeepLearning

  bayesian-deep-learningbayesian-neural-networkuncertainty-quantificationdeep-learningtensorflow-probabilitytensorflowhigh-energy-physicsparticle-physics
  Language:Jupyter Notebook 3

• abhimanyu911 / bayesian_sdss

  A Bayesian CNN approach to SDSS image data classification

  bayesian-convolution-networkbayesian-inferencebayesian-neural-networksbayesian-statisticsensembling-methodsentropygalaxy-classificationgalaxy-zootensorflowtensorflow-probability
  Language:Jupyter Notebook 2

• akensert / reinforceable

  Deep reinforcement learning implementations using TensorFlow and TensorFlow probability.

  deep-learningkerasreinforcement-learningtensorflowtensorflow-probability
  Language:Python 2

• danftang / MutableCategoricalDistribution

  A categorical distribution with efficient sampling and modification of category probabilities

  probabilistic-programmingpymc3tensorflow-probabilityhuffman-codingadaptive-huffmancategorical-distributions
  Language:C++ 2

• jilljenn / vae

  Variational Factorization Machines in TensorFlow and PyTorch

  factorization-machinespytorchtensorflowtensorflow-probabilitytorch-distributionsvariational-inference
  Language:Python 2

• 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.

  deep-reinforcement-learningkeras-tensorflowpythontensorflow-probabilitytensorflow2
  Language:Python 2

• OpenSUTD / ProbStats-with-TFP

  Prob&Stats with TensorFlow Probability

  istdtensorflowtensorflow-probabilityprobabilitygoogle-colab
  Language:Jupyter Notebook 2

• slowmoyang / bayesian-deep-learning

  tensorflowtensorflow-probabilitybayesian-deep-learningout-of-distribution-detectionanomaly-detectionuncertainty-quantification
  Language:Python 2

• TheUnsolvedDev / ProbabilisticMadness

  Statistics and Machine Learning in depth analysis with Tensorflow Probability

  bayesianhamiltonian-monte-carlomonte-carlotensorflow-probabilitytensorflow2distributionsmaximum-a-posteriori-estimationmaximum-likelihood-estimation
  Language:Python 2

• wataruhashimoto52 / nmf_tfp

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

  tensorflowtensorflow2tensorflow-probabilityrecommendationbayesian-inferencevariational-inferencenon-negative-matrix-factorization
  Language:Python 2

• hosford42 / TensorFlowUtilities

  Assorted useful tensorflow functions and keras layers

  tensorflow-probabilitytensorflow2
  Language:Python 1

• MarcoRiggirello / diglm

  Deep Invertible Generalized Linear Model implemented on top of tensorflow_probability

  glmnormalizing-flowstensorflow-probability
  Language:Jupyter Notebook 1

• 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.

  bayesian-statisticsintergalactic-mediumkerasregressionspectratensorflow-probability
  Language:Python 1