baccuslab / shannon
A python package for computing the mutual information and entropy for continuous and discrete data.
☆34Updated 7 years ago
Alternatives and similar repositories for shannon:
Users that are interested in shannon are comparing it to the libraries listed below
- ☆55Updated 7 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 11 years ago
- Collapsed Variational Bayes☆70Updated 5 years ago
- Variational Autoencoder for Dimensionality Reduction of Time-Series☆186Updated 2 years ago
- Clustering time series using Gaussian processes and Variational Bayes.☆39Updated 4 years ago
- ☆74Updated 6 years ago
- Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables☆13Updated 7 years ago
- Gaussian process regression code.☆24Updated 11 years ago
- local non-uniformity correction for mutual information estimation☆70Updated 3 years ago
- ☆10Updated 8 years ago
- ☆12Updated 7 years ago
- Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood☆94Updated 7 years ago
- Probabilistic Principal Component Analysis☆62Updated 8 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆31Updated 8 years ago
- Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'☆38Updated 6 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆82Updated 4 years ago
- State space modeling with recurrent neural networks☆45Updated 7 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Versatile Nonlinear Feature Selection Algorithm for High-dimensional Data☆182Updated 3 years ago
- Unsupervised feature learning based on sparse-filtering☆55Updated 10 years ago
- ☆68Updated last year
- Code for AutoGP☆26Updated 5 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 8 months ago
- Repository for 'Interpretable embeddings from molecular simulations using gaussian mixture variational autoencoders'☆20Updated 5 years ago
- Deep Gaussian Processes in matlab☆92Updated 3 years ago
- REGAIN (Regularised Graphical Inference)☆29Updated last year
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆99Updated 5 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆66Updated 7 years ago
- A practical tool for Maximal Information Coefficient (MIC) analysis☆132Updated last year
- Dirichlet Process Mixture using PVI, SMC, Variational☆15Updated 10 years ago