msmbuilder / vdeLinks
Variational Autoencoder for Dimensionality Reduction of Time-Series
☆188Updated 3 years ago
Alternatives and similar repositories for vde
Users that are interested in vde are comparing it to the libraries listed below
Sorting:
- TensorFlow implementation of the SOM-VAE model as described in https://arxiv.org/abs/1806.02199☆196Updated 2 years ago
- Bayesian optimization for Python☆246Updated 3 years ago
- This project provides Slow Feature Analysis as a scikit-learn-style package.☆41Updated last year
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 11 months ago
- Kalman Variational Auto-Encoder☆136Updated 6 years ago
- Repository for 'Interpretable embeddings from molecular simulations using gaussian mixture variational autoencoders'☆20Updated 5 years ago
- Foundations and Applications☆98Updated 5 years ago
- ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'☆91Updated 5 years ago
- Versatile Nonlinear Feature Selection Algorithm for High-dimensional Data☆185Updated 3 years ago
- Minimum description length principle algorithm in Python, for optimal binning of continuous variables☆60Updated 2 years ago
- Code associated with ACM-CHIL 21 paper 'T-DPSOM - An Interpretable Clustering Method for Unsupervised Learning of Patient Health States'☆69Updated 4 years ago
- Probabilistic Principal Component Analysis☆63Updated 8 years ago
- Heteroscedastic Bayesian Optimisation in Numpy☆21Updated 2 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- Deep Gaussian Processes in Python☆234Updated 4 years ago
- Clean repo for tensor-train RNN implemented in TensorFlow☆68Updated 5 years ago
- Deep Markov Models☆132Updated 6 years ago
- Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood☆93Updated 7 years ago
- Structured Inference Networks for Nonlinear State Space Models☆272Updated 7 years ago
- Sequential Neural Likelihood☆40Updated 5 years ago
- A Recurrent Latent Variable Model for Sequential Data☆27Updated 7 years ago
- Python library for working with kernel methods in machine learning☆120Updated 6 years ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆197Updated 2 years ago
- Variational Fourier Features☆86Updated 4 years ago
- Toy Examples of Conditional Density Estimation with Bayesian Normalizing flows☆22Updated 6 years ago
- InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy☆148Updated 11 months ago
- Using Bayesian Optimization to optimize hyper parameter in Keras-made neural network model.☆57Updated 7 years ago
- ☆91Updated 2 years ago
- ☆59Updated 6 years ago
- A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)☆349Updated 8 years ago