Implementing a bayesian neural network in TensorFlow
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Updated
May 23, 2018 - Python
Implementing a bayesian neural network in TensorFlow
Keras, Tensorflow eager execution implementation of Categorical Variational Autoencoder
Keras, Tensorflow eager execution implementation of Neural Processes
Jupyter Notebooks that show the basic functionalities of edward2
Prob&Stats with TensorFlow Probability
TensorFlow Probability Tutorial
A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.
Distributed Training of Bayesian Neural Networks at Scale
Tensor utilities, reinforcement learning, and more!
Built a regression model that predicts the expected days of hospitalization time and an uncertainty range estimation.
A generalized framework for generative and probabilistic modelling for training reinforcement learning agents in TensorFlow 2.
Probabilistic programming, Bayesian Thinking, Bayesian Data Analysis and Applications
Statistics MSc Project (2020): Audio Source Separation
Task in belong laboratory (related: https://github.com/chiru1221/LabStudyTask2020)
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.
Patient Selection for Diabetes Drug Trial is part of the AI for Healthcare nanodegree program from Udacity.
Markov chain Monte Carlo and variational inference.
Statistical Rethinking (2nd Ed) with Tensorflow Probability
Clustered Gaussian Process Regression in TFP
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