[TMLR' 24] High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy
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Updated
Jun 19, 2024 - Python
[TMLR' 24] High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy
Implements "Clustering a Million Faces by Identity"
Simple and efficient Python package for modeling d-dimensional Bravais lattices in solid state physics.
Bayesian optimization with Standard Gaussian Processes on high dimensional benchmarks
A high-performance distributed deep learning system targeting large-scale and automated distributed training.
Locally Sensitive Hashing based embedding for High Dimensional Multivariate Time Series
flameplot is a python package for the quantification of local similarity across two maps or embeddings.
A Bayesian multiscale deep learning framework for flows in random media
A fast, accurate, and modularized dimensionality reduction approach based on diffusion harmonics and graph layouts. Escalates to millions of samples on a personal laptop. Adds high-dimensional big data intrinsic structure to your clustering and data visualization workflow.
A numerical library for High-Dimensional option Pricing problems, including Fourier transform methods, Monte Carlo methods and the Deep Galerkin method
Video Input Generative Adversarial Imitation Learning
Lossless conversion algorithm for converting Cortical Learning Algorithm binary vectors to Modular Composite Representation vectors. Implements Integer Sparse Distributed Memory.
A q-quantile estimator for high-dimensional distributions
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