achab / nphcLinks
NPHC
☆17Updated 4 years ago
Alternatives and similar repositories for nphc
Users that are interested in nphc are comparing it to the libraries listed below
Sorting:
- ☆77Updated 7 years ago
- Exponential family embeddings (Poisson or Bernoulli) for discrete data☆32Updated 6 years ago
- Code for the icml paper "zero inflated exponential family embedding"☆29Updated 7 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆69Updated 7 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017☆36Updated 6 years ago
- MADE: Masked Autoencoder for Distribution Estimation☆102Updated 5 years ago
- Variational Fourier Features☆85Updated 4 years ago
- Python implementation of Markov Jump Hamiltonian Monte Carlo☆24Updated 8 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago
- Poisson-Gamma dynamical systems☆17Updated 8 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆106Updated 7 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 11 years ago
- This is code associated with the paper: Broderick, T, Boyd, N, Wibisono, A, Wilson, AC, and Jordan, MI. Streaming variational Bayes. Neur…☆41Updated 10 years ago
- A toolbox of Hawkes processes☆115Updated 7 years ago
- The Matlab Code for the ICML 2015 paper "Scalable Deep Poisson Factor Analysis for Topic Modeling"☆19Updated 9 years ago
- ☆12Updated 2 years ago
- Bayesian Poisson Tucker decomposition☆17Updated 8 years ago
- Code for "Sequential Neural Models with Stochastic Layers"☆117Updated 8 years ago
- Variational inference for Gaussian mixture models☆36Updated 11 years ago
- Scalable GP Adapter for Time Series Classification☆13Updated 7 years ago
- Bayesian Poisson tensor factorization☆61Updated 9 months ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆38Updated 8 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Deep generative models for semi-supervised learning.☆108Updated 8 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago