steveli / gp-adapterLinks
Scalable GP Adapter for Time Series Classification
☆13Updated 7 years ago
Alternatives and similar repositories for gp-adapter
Users that are interested in gp-adapter are comparing it to the libraries listed below
Sorting:
- Code for the icml paper "zero inflated exponential family embedding"☆29Updated 7 years ago
- Variational Fourier Features☆86Updated 4 years ago
- Implementation of linear CorEx and temporal CorEx.☆37Updated 3 years ago
- Exponential family embeddings (Poisson or Bernoulli) for discrete data☆32Updated 6 years ago
- Wasserstein regularization for sparse multi-task regression☆15Updated 5 years ago
- ☆12Updated 2 years ago
- Dirichlet Process Mixture using PVI, SMC, Variational☆15Updated 11 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- ☆18Updated 7 years ago
- This contains my M.Tech project work on using Deep Leanring for learning graph representations. Data will be provided on request☆33Updated 8 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆39Updated 8 years ago
- Bayesian Poisson Tucker decomposition☆17Updated 8 years ago
- Sparse Beta-Divergence Tensor Factorization Library☆48Updated 2 months ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Movies Recommendation with Hierarchical Poisson Factorization in Edward☆18Updated 8 years ago
- Python code for implementing embeddings in the Wasserstein space of elliptical distributions☆11Updated 5 years ago
- TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper☆51Updated 6 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 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
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago
- Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018☆26Updated 7 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- 🧹 Formerly for binary classification with noisy labels. Replaced by cleanlab.☆82Updated 3 years ago
- Columbia Advanced Machine Learning Seminar☆24Updated 7 years ago
- a deep recurrent model for exchangeable data☆34Updated 5 years ago
- Code for my paper "Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression"☆11Updated 11 years ago
- Bernoulli Embeddings for Text☆83Updated 7 years ago
- ☆74Updated 6 years ago
- An iterative neural autoregressive distribution estimator (NADE-K)☆26Updated 10 years ago