no code implementations • 30 Mar 2024 • Geoffrey S. H. Cruttwell, Bruno Gavranovic, Neil Ghani, Paul Wilson, Fabio Zanasi
We propose a categorical semantics for machine learning algorithms in terms of lenses, parametric maps, and reverse derivative categories.
1 code implementation • 3 Mar 2023 • Mahdi Gilany, Paul Wilson, Andrea Perera-Ortega, Amoon Jamzad, Minh Nguyen Nhat To, Fahimeh Fooladgar, Brian Wodlinger, Purang Abolmaesumi, Parvin Mousavi
We analyze this method using a dataset of micro-ultrasound acquired from 578 patients who underwent prostate biopsy, and compare our model to baseline models and other large-scale studies in the literature.
no code implementations • 11 Dec 2022 • Mike Thelwall, Kayvan Kousha, Mahshid Abdoli, Emma Stuart, Meiko Makita, Paul Wilson, Jonathan Levitt, Petr Knoth, Matteo Cancellieri
National research evaluation initiatives and incentive schemes have previously chosen between simplistic quantitative indicators and time-consuming peer review, sometimes supported by bibliometrics.
no code implementations • 11 Dec 2022 • Mike Thelwall, Kayvan Kousha, Mahshid Abdoli, Emma Stuart, Meiko Makita, Paul Wilson, Jonathan Levitt
This document describes strategies for using Artificial Intelligence (AI) to predict some journal article scores in future research assessment exercises.
no code implementations • 21 Jul 2022 • Mahdi Gilany, Paul Wilson, Amoon Jamzad, Fahimeh Fooladgar, Minh Nguyen Nhat To, Brian Wodlinger, Purang Abolmaesumi, Parvin Mousavi
We train a deep model using a co-teaching paradigm to handle noise in labels, together with an evidential deep learning method for uncertainty estimation.
no code implementations • 12 Mar 2022 • Paul Wilson, Fabio Zanasi
Reverse derivative categories (RDCs) have recently been shown to be a suitable semantic framework for studying machine learning algorithms.
no code implementations • 13 Jun 2021 • Dan Shiebler, Bruno Gavranović, Paul Wilson
Over the past two decades machine learning has permeated almost every realm of technology.
no code implementations • 2 Mar 2021 • G. S. H. Cruttwell, Bruno Gavranović, Neil Ghani, Paul Wilson, Fabio Zanasi
We propose a categorical semantics of gradient-based machine learning algorithms in terms of lenses, parametrised maps, and reverse derivative categories.
no code implementations • 26 Jan 2021 • Paul Wilson, Fabio Zanasi
Our motivating example is boolean circuits: we show how our algorithm can be applied to such circuits by using the theory of reverse differential categories.
no code implementations • 1 Oct 2012 • Greg Wilson, D. A. Aruliah, C. Titus Brown, Neil P. Chue Hong, Matt Davis, Richard T. Guy, Steven H. D. Haddock, Katy Huff, Ian M. Mitchell, Mark Plumbley, Ben Waugh, Ethan P. White, Paul Wilson
Scientists spend an increasing amount of time building and using software.
Mathematical Software Software Engineering