Manifold optimization based Optimal Transport

Primal-dual Algorithms for Non-negative Matrix Factorization with the Kullback-Leibler Divergence

Unsupervised image segmentation by applying topological data analysis techniques.

Sparse simplex projection-based Wasserstein k-means

Consistency-aware and inconsistency-aware graph-based multi-view clustering

WIP

Graph Neural Network Library for PyTorch

A curated list of network embedding techniques.

The source codes for D2AGE model. Distance-aware DAG Embedding for Proximity Search on Heterogeneous Graphs.

InfiniteBoost: building infinite ensembles with gradient descent

LIBS2ML: A Library for Scalable Second Order Machine Learning Algorithms

Look Ahead Hamiltonian Monte Carlo

Matlab Implementation for Stochastic Gradient Hamiltonian Monte Carlo

MCMC for posterior distribution sampling

tensor-tensor product toolbox

A Dual Framework for Low-rank Tensor Completion

Subsampled Riemannian trust-region (RTR) algorithms

Simple MATLAB toolbox for deep learning network: Version 1.0.3

Computations and statistics on manifolds with geometric structures.

Side Information infused Incremental Tensor Analysis

A manifold optimization library for deep learning

Subspace clustering through the deep learning approach

Riemannian stochastic optimization algorithms: Version 1.0.3

Optimization algorithms for hybrid precoding in mmWave MIMO systems: Version 1.1.0

Code for the paper "Tensor Regression Networks with various Low-Rank Tensor Approximations"

Tensor methods in Python with TensorLy