tonyduan / matrix-completionLinks
Lightweight Python library for in-memory matrix completion.
☆107Updated 2 years ago
Alternatives and similar repositories for matrix-completion
Users that are interested in matrix-completion are comparing it to the libraries listed below
Sorting:
- learning point processes by means of optimal transport and wasserstein distance☆54Updated 7 years ago
- Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'☆38Updated 7 years ago
- Detecting Statistical Interactions from Neural Network Weights☆49Updated 5 years ago
- Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood☆95Updated 8 years ago
- Coresets☆38Updated 3 years ago
- Neural Graph Differential Equations (Neural GDEs)☆212Updated 4 years ago
- ☆57Updated 8 years ago
- A Persistent Weisfeiler–Lehman Procedure for Graph Classification☆63Updated 4 years ago
- A Pytorch implementation of missing data imputation using optimal transport.☆105Updated 4 years ago
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.☆41Updated last year
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆58Updated 5 years ago
- Variational Inference in Gaussian Mixture Model☆61Updated 5 years ago
- A Wasserstein Subsequence Kernel for Time Series.☆21Updated last year
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 6 years ago
- Clean repo for tensor-train RNN implemented in TensorFlow☆69Updated 6 years ago
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆126Updated 2 months ago
- ☆23Updated 2 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆25Updated 2 years ago
- Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model☆103Updated last year
- Multi-task learning via Structural Regularization☆136Updated 5 years ago
- Experimental Codes for Temporal Regularized Matrix Factoriztion for High-dimensional Time Series Prediction.☆79Updated 6 years ago
- Deep neural network kernel for Gaussian process☆212Updated 5 years ago
- An encoder-decoder framework for learning from incomplete data☆45Updated 2 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆37Updated 5 years ago
- D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, NeurIPS 2019☆145Updated 5 years ago
- Automated Scalable Bayesian Inference☆131Updated 4 years ago
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.☆40Updated 4 years ago
- ☆43Updated 6 years ago
- MisGAN: Learning from Incomplete Data with GANs☆80Updated 2 years ago
- A package for Multiple Kernel Learning in Python☆131Updated 2 years ago