Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
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Oct 19, 2024 - Python
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tensorflow-probability
Here are 47 public repositories matching this topic...
Statistical Rethinking (2nd Ed) with Tensorflow Probability
tensorflow tutorials bayesian-inference variational-inference bayesian-statistics markov-chain-monte-carlo tensorflow-probability statistical-rethinking
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Jan 19, 2022 - Jupyter Notebook
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.
machine-learning tensorflow keras multivariate-distributions probabilistic-programming poisson-distribution univariate-distributions bernoulli-distribution tfp tensorflow-probability tensorflow2 binomial-distributions probabilistic-deep-learning deep-probabilistic-models probabilistic-layers
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Nov 27, 2024 - Jupyter Notebook
Machine learning model for predicting Serie A players performance in a match, in terms of Fantacalcio (italian fantasy football) scores.
python machine-learning ai neural-network tensorflow fantasy-football serie-a fantacalcio tensorflow-probability
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Oct 5, 2023 - Jupyter Notebook
TensorFlow Probability Tutorial
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Oct 17, 2019 - Jupyter Notebook
A Python package for adding uncertainties to neural network models of chemical systems.
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Jul 5, 2022 - PureBasic
This repo contains the notebooks that is used in Medium posts.
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Apr 11, 2022 - Jupyter Notebook
A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.
binary tensorflow vae variational-inference variational-autoencoder bernoulli concrete-distribution tensorflow-eager tensorflow-probability
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Feb 1, 2020 - Python
Built a regression model that predicts the expected days of hospitalization time and an uncertainty range estimation.
tensorflow regression feature-engineering uncertainty-estimation tensorflow-probability ehr-data ai-for-healthcare
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Jul 14, 2020 - Jupyter Notebook
A normalizing flow using Bernstein polynomials for conditional density estimation.
machine-learning regression probabilistic-modeling tensorflow-probability tensorflow2 bernstein-polynomials
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Oct 18, 2024 - Jupyter Notebook
Implementing a bayesian neural network in TensorFlow
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May 23, 2018 - Python
Distributed Training of Bayesian Neural Networks at Scale
data-science machine-learning computer-vision tensorflow distributed-computing mnist uncertainty-quantification bayesian-networks variational-inference horovod tensorflow-probability
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May 26, 2020 - Python
Tensor utilities, reinforcement learning, and more!
machine-learning reinforcement-learning deep-learning tensorflow gym tensorflow-probability eager-execution
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Jun 25, 2020 - Python
TensorFlow ML - an abstract implementation of commonly used machine learning algorithms using TensorFlow. Feel free to contribute! (Work in Progress)
numpy machine-learning-algorithms keras tensorflow-probability tensorflow2 tensorflow-decision-forests
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Aug 7, 2023 - Python
A Bayesian Convolutional Neural Network model for classifying Cataract in Ocular Disease with measurements of uncertainty
opencv machine-learning tensorflow keras bayesian-methods classification image-classification convolutional-neural-networks uncertainty-quantification tensorflow-probability uncertainty-visualisation probabilistic-machine-learning bayesian-probabilistic-models
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Jun 15, 2022 - Jupyter Notebook
Keras, Tensorflow eager execution implementation of Neural Processes
time-series neural-network tensorflow keras regression toronto variational-inference variational-autoencoder tensorflow-probability krist-papadopoulos neural-processes
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Oct 12, 2018 - Python
Jupyter Notebooks that show the basic functionalities of edward2
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Dec 10, 2018 - Jupyter Notebook
Keras, Tensorflow eager execution implementation of Categorical Variational Autoencoder
tensorflow keras mnist generative-model toronto variational-inference variational-autoencoder gumbel-softmax categorical tensorflow-eager tensorflow-probability krist-papadopoulos categorical-variational-autoencoder
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Sep 25, 2018 - Python
Code accompanying my 2021 ASA SDSS paper
neural-network neural-networks causality causality-analysis causal-inference merchandising structural-equation-modeling causal-models directed-acyclic-graph causal-networks tensorflow-probability
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May 18, 2022 - Python
Statistics MSc Project (2020): Audio Source Separation
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Dec 13, 2020 - Python
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