high-dimensional

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

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

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

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

MATLAB library for large Bayesian VARs: samplers, shrinkage priors, stochastic volatility, marginal likelihoods and forecasting, with examples, tutorials and the replication packages from joshuachan.org.

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

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

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