Vertical Slice Architecture solution template in .NET 10
Torchhd is a Python library for Hyperdimensional Computing and Vector Symbolic Architectures
Voice stress analysis (VSA) aims to differentiate between stressed and non-stressed outputs in response to stimuli (e.g., questions posed), with high stress seen as an indication of deception. In this work, we propose a deep learning-based psychological stress detection model using speech signals. With increasing demands for communication betwee…
The Fuzzy-Pattern Tsetlin Machine library, with zero external dependencies, performs blazingly fast.
Rohde & Schwarz SCPI Driver (in Python)
Holographic Reduced Representations
"Commit information, not traffic" - Vector–Scalar Accumulator (VSA) is a lightweight algorithmic primitive that eliminates write amplification and hot-row contention in high-frequency systems
Domain-Agnostic Supervised Learning with Hyperdimensional Computing
The holographic core for leOS
Thesis project on the development of a framework for Value-Set Analysis
Holographic vectors you can compute with. Bind structure, bundle sets, unbind components cross NumPy, PyTorch, and JAX.
Sparse binary hypervectors and associated learners.
A high-performance autonomous bitwise model leveraging Vector Symbolic Architectures (VSA) and Hyperdimensional Computing (HDC). Built in Rust.
Volume Spread Analysis (VSA) is a powerful trading methodology that examines the relationship between volume, price spread (range), and closing price to identify market reversals, continuations, and potential manipulation by "smart money."
Video streaming web application [VSA], through HLS, using AES-128 encryption
An extended note on using Vector Symbolic Architectures to implement Next Generation Reservoir Computing
a basic VSA sample in c#
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