Search Results for author: Andrew Thompson

Found 8 papers, 2 papers with code

AAD-LLM: Adaptive Anomaly Detection Using Large Language Models

no code implementations1 Nov 2024 Alicia Russell-Gilbert, Alexander Sommers, Andrew Thompson, Logan Cummins, Sudip Mittal, Shahram Rahimi, Maria Seale, Joseph Jaboure, Thomas Arnold, Joshua Church

The research aims to improve the transferability of anomaly detection models by leveraging Large Language Models (LLMs) and seeks to validate the enhanced effectiveness of the proposed approach in data-sparse industrial applications.

Anomaly Detection

Trustworthy Artificial Intelligence in the Context of Metrology

no code implementations14 Jun 2024 Tameem Adel, Sam Bilson, Mark Levene, Andrew Thompson

We then discuss three research areas within TAI that we are working on at NPL, and examine the certification of AI systems in terms of adherence to the characteristics of TAI.

Uncertainty Quantification

A divide-and-conquer algorithm for binary matrix completion

no code implementations9 Jul 2019 Melanie Beckerleg, Andrew Thompson

We propose an algorithm for low rank matrix completion for matrices with binary entries which obtains explicit binary factors.

Low-Rank Matrix Completion Recommendation Systems

Adaptive DCTNet for Audio Signal Classification

1 code implementation13 Dec 2016 Yin Xian, Yunchen Pu, Zhe Gan, Liang Lu, Andrew Thompson

Its output feature is related to Cohen's class of time-frequency distributions.

Sound

DCTNet and PCANet for acoustic signal feature extraction

1 code implementation28 Apr 2016 Yin Xian, Andrew Thompson, Xiaobai Sun, Douglas Nowacek, Loren Nolte

We introduce the use of DCTNet, an efficient approximation and alternative to PCANet, for acoustic signal classification.

Classification General Classification

Sketching for Sequential Change-Point Detection

no code implementations25 May 2015 Yang Cao, Andrew Thompson, Meng Wang, Yao Xie

We study sequential change-point detection procedures based on linear sketches of high-dimensional signal vectors using generalized likelihood ratio (GLR) statistics.

Change Point Detection

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