A high-performance distributed deep learning system targeting large-scale and automated distributed training.
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Updated
Dec 13, 2025 - Python
A high-performance distributed deep learning system targeting large-scale and automated distributed training.
Implements "Clustering a Million Faces by Identity"
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
Bayesian optimization with Standard Gaussian Processes on high dimensional benchmarks
[TMLR' 24] High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy
KNRScore is a Python package for computing K-Nearest-Rank Similarity, a metric that quantifies local structural similarity between two maps or embeddings.
[AAAI' 25] BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided Direction Lines and Subspace Embeddings
Video Input Generative Adversarial Imitation Learning
Holographic vectors you can compute with. Bind structure, bundle sets, unbind components cross NumPy, PyTorch, and JAX.
[ECAI' 25]: MOCA-HESP: Meta High-dimensional Bayesian Optimization for Combinatorial and Mixed Spaces via Hyper-ellipsoid Partitioning
A q-quantile estimator for high-dimensional distributions
Locally Sensitive Hashing based embedding for High Dimensional Multivariate Time Series
Reference implementation of the Spiral–HDAG–Coupling architecture. It combines a verifiable ledger, a tensor-based Hyperdimensional DAG, and Time Information Crystals to provide a new kind of memory layer for Machine Learning. With integrated Zero-Knowledge ML, the system enables trustworthy, auditable, and privacy-preserving AI pipelines.
High Dimensional Orthogonal Vectors Analysis
Lossless conversion algorithm for converting Cortical Learning Algorithm binary vectors to Modular Composite Representation vectors. Implements Integer Sparse Distributed Memory.
A Bayesian multiscale deep learning framework for flows in random media
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