satwik77 / libnmf
Optimization and Regularization variants of Non-negative Matrix Factorization (NMF)
☆32Updated 5 years ago
Related projects: ⓘ
- Implementation of the Multiscale Laplacian Graph Kernel☆17Updated 4 years ago
- Code for the icml paper "zero inflated exponential family embedding"☆28Updated 6 years ago
- Vector-Space Markov Random Fields☆21Updated 9 years ago
- Graph Feature Representation/Vector Based On The Family Of Graph Spectral Distances (NIPS 2017).☆24Updated 4 years ago
- Variational Auto-encoder with Non-parametric Bayesian Prior☆42Updated 7 years ago
- Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)☆38Updated 7 years ago
- The Matlab Code for the ICML 2015 paper "Scalable Deep Poisson Factor Analysis for Topic Modeling"☆19Updated 9 years ago
- Movies Recommendation with Hierarchical Poisson Factorization in Edward☆18Updated 7 years ago
- Python implementation of Robust Continuous Clustering☆101Updated 5 years ago
- Fast graph-regularized matrix factorization☆20Updated 11 months ago
- ☆19Updated 2 years ago
- Mixed Membership Stochastic Blockmodel Implementation with 3 Inference Schemes☆24Updated 9 years ago
- Summaries and minimal implementations of ML / statistics research articles.☆38Updated 3 years ago
- Echo Noise Channel for Exact Mutual Information Calculation☆17Updated 4 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆26Updated 3 years ago
- Implementation of "Variational Inference for Monte Carlo Objectives"☆21Updated 4 years ago
- ☆11Updated 6 years ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Variational Autoencoders & Normalizing Flows Project☆19Updated 7 years ago
- investigating use of variational auto encoders with multinomial latent variables for unsupervised data.☆24Updated 7 years ago
- Code for AISTATS 2017 paper on "Conjugate-Computation Variational Inference"☆18Updated 4 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆62Updated 6 years ago
- Causal Inference & Deep Learning, MIT IAP 2018☆85Updated 6 years ago
- Source for experiments in the Additive Gaussian process paper, as well as extensions relating to dropout.☆21Updated 10 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆66Updated 5 years ago
- Collapsed Variational Bayes☆67Updated 4 years ago
- Semi supervised learning on graphs☆35Updated 6 years ago
- Variational Autoencoders with Gaussian Mixture Latent Space☆36Updated 7 years ago
- Learning neural network embeddings in hyperbolic spaces☆14Updated 4 years ago