Gavin Brown

5.2k citations

65 papers · 2.7k indexed · 2 hit papers · h-index 21

Impact in

Artificial Intelligence top 0.5%
- Machine Learning and Data Classification
- Neural Networks and Applications
- Imbalanced Data Classification Techniques
- Evolutionary Algorithms and Applications
- Metaheuristic Optimization Algorithms Research
- Anomaly Detection Techniques and Applications
Computer Vision and Pattern Recognition top 1%
- Face and Expression Recognition

Papers in

Artificial Intelligence 43
- Machine Learning and Data Classification 16
- Neural Networks and Applications 13
- Evolutionary Algorithms and Applications 11
- Metaheuristic Optimization Algorithms Research 7
- Imbalanced Data Classification Techniques 4
Hardware and Architecture 7
- Parallel Computing and Optimization Techniques 7

Co-authors: Jeremy Wyatt Mikel Luján Adam Pocock Mingjie Zhao Xin Yao Rachel Harris Peter Tiňo Konstantinos Sechidis
Journals: Machine Learning (4 papers)Journal of Machine Learning Research (4 papers)Information Sciences (2 papers)Nature Electronics (2 papers)Scientific Reports (1 paper)
Partner nations: United Kingdom United States Spain

In The Last Decade

Gavin Brown

63 papers receiving 2.6k citations

Hit Papers

align trajectories log scale

Conditional likelihood maximisation: a unifying framework for information theoretic feature selection 2012 · 783 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2012 Journal of Machine Learning Research
2004 Information Fusion

Peers

Countries citing papers authored by Gavin Brown

Since Specialization

Citations

This map shows the geographic impact of Gavin Brown's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gavin Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gavin Brown more than expected).

Fields of papers citing papers by Gavin Brown

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gavin Brown. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gavin Brown. The network helps show where Gavin Brown may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Gavin Brown, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gavin Brown Line = papers co-authored together Gavin Brown links everyone, so they are left out of the graph.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work
1	Predicting Domestic Abuse (Fairly) and Police Risk Assessment Psychosocial Intervention ·Mewa, Gavin Brown, Juanjo Medina	2022	5
2	Dashing Hopes? the Predictive Accuracy of Domestic Abuse Risk Assessment by Police The British Journal of Criminology ·Mewa, Juanjo Medina, Gavin Brown	2019	37
3	Hybrid extreme learning machine approach for heterogeneous neural networks Neurocomputing ·Vasileios Christou, Markos G. Tsipouras, Νικόλαος Γιαννακέας, Alexandros T. Tzallas, Gavin Brown	2019	20
4	Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid UNICA IRIS Institutional Research Information System (University of Cagliari) ·Marco Melis, Ambra Demontis, Battista Biggio, Gavin Brown, Giorgio Fumera, Fabio Roli	2018	44
5	On the stability of feature selection algorithms Journal of Machine Learning Research ·W. R. Gerard, Konstantinos Sechidis, Gavin Brown	2017	47
6	Individual Confidence-Weighting and Group Decision-Making Trends in Ecology & Evolution ·James A. R. Marshall, Gavin Brown, Andrew N. Radford	2017	33
7	Exploring the Relationship Between Eye Movements and Electrocardiogram Interpretation Accuracy Scientific Reports ·Alan Davies, Gavin Brown, Markel Vigo, Simon Harper, И. Ю. Иванова, M Martínez De Guzmán, Elspeth J. R. Hill, Caroline Jay	2016	11
8	Modular Autoencoders for Ensemble Feature Extraction Research Explorer (The University of Manchester) ·Yanan Sheng, Gavin Brown	2015	2
9	Predicting performance of OWL reasoners: locally or globally? Research Explorer (The University of Manchester) ·Gloria Elvira Granillo Villegas, Ulrike Sattler, Gavin Brown	2014	8
10	Predicting OWL Reasoners: Locally or Globally? Research Explorer (The University of Manchester) ·Gloria Elvira Granillo Villegas, Ulrike Sattler, Gavin Brown	2014	1
11	Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition - Volume 8621 Pasi Fränti, Gavin Brown, Marco Loog, Francisco Escolano, Marcello Pelillo	2014	1
12	Beyond Fano's inequality: bounds on the optimal F-score, BER, and cost-sensitive risk and their implications Journal of Machine Learning Research ·Mingjie Zhao, Ė. A. Symonovich, Adam Pocock, Gavin Brown	2013	27
13	Conditional likelihood maximisation: a unifying framework for information theoretic feature selection Journal of Machine Learning Research ·Gavin Brown, Adam Pocock, Mingjie Zhao, Mikel Luján Hit paper breakdown →	2012	783
14	Informative Priors for Markov Blanket Discovery Research Explorer (The University of Manchester) ·Adam Pocock, Mikel Luján, Gavin Brown	2012	2
15	Boosting as a Product of Experts Research Explorer (The University of Manchester) ·Ė. A. Symonovich, Gavin Brown, Tim Kovacs	2012	3
16	A New Perspective for Information Theoretic Feature Selection International Conference on Artificial Intelligence and Statistics ·Gavin Brown	2009	106
17	Sparse Distributed Memory Using Rank-Order Neural Codes IEEE Transactions on Neural Networks ·Steve Furber, Gavin Brown, 則夫長濱, 前田文昭, Philip J. Marshall, Jonathan Shapiro	2007	11
18	Managing Diversity in Regression Ensembles Journal of Machine Learning Research ·Gavin Brown, Jeremy Wyatt, Peter Tiňo	2005	238
19	Diversity in Neural Network Ensembles OpenGrey (Institut de l'Information Scientifique et Technique) ·Gavin Brown	2004	89
20	The use of the ambiguity decomposition in neural network ensemble learning methods International Conference on Machine Learning ·Gavin Brown, Jeremy Wyatt	2003	15

About Gavin Brown

Gavin Brown is a scholar working on Artificial Intelligence, Hardware and Architecture, Software, Computer Vision and Pattern Recognition and Statistics and Probability, having authored 65 papers that have together received 2.7k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (16 papers), Neural Networks and Applications (13 papers), Evolutionary Algorithms and Applications (11 papers), Face and Expression Recognition (10 papers), Metaheuristic Optimization Algorithms Research (7 papers), Parallel Computing and Optimization Techniques (7 papers), Imbalanced Data Classification Techniques (4 papers) and Rough Sets and Fuzzy Logic (4 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Computer Vision and Pattern Recognition (733 citations), Signal Processing (228 citations), Hardware and Architecture (102 citations) and Software (57 citations). Gavin Brown has collaborated with scholars based in United Kingdom, United States and Spain. Frequent co-authors include Jeremy Wyatt, Mikel Luján, Adam Pocock, Mingjie Zhao, Xin Yao, Rachel Harris, Peter Tiňo, Konstantinos Sechidis, Jeremy Singer and James A. R. Marshall. Their work appears in journals such as Machine Learning, Journal of Machine Learning Research, Information Sciences, Nature Electronics and Scientific Reports.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact