A Flexible and Powerful Parameter Server for large-scale machine learning

A high-performance distributed deep learning system targeting large-scale and automated distributed training.

Octree/Quadtree/N-dimensional linear tree

Implements "Clustering a Million Faces by Identity"

Open and explore HDF5 files in JupyterLab. Can handle very large (TB) sized files, and datasets of any dimensionality

Time-HD-Lib: A Library for High-Dimensional Time Series Forecasting

Deprecated in favour of TopoMetry: https://github.com/davisidarta/topometry

Simple and efficient Python package for modeling d-dimensional Bravais lattices in solid state physics.

DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems

A numerical library for High-Dimensional option Pricing problems, including Fourier transform methods, Monte Carlo methods and the Deep Galerkin method

Particle Swarm Optimization Visualization

Bayesian optimization with Standard Gaussian Processes on high dimensional benchmarks

[TMLR' 24] High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy

Numerical illustration of a novel analysis framework for consensus-based optimization (CBO) and numerical experiments demonstrating the practicability of the method

DataHigh: A graphical user interface for visualizing and interacting with high-dimensional neural activity

BioMM: Biological-informed Multi-stage Machine learning framework for phenotype prediction using omics data

Controlled Invariant Sets in Two Moves

KNRScore is a Python package for computing K-Nearest-Rank Similarity, a metric that quantifies local structural similarity between two maps or embeddings.

Regularization Paths for Huber Loss Regression and Quantile Regression Penalized by Lasso or Elastic-Net

Implementation of the FNETS methodology proposed in Barigozzi, Cho and Owens (2024) for network estimation and forecasting of high-dimensional time series