Neil Dhir

According to our database, Neil Dhir authored at least 18 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Near Real-Time Social Distance Estimation In London.

James Walsh, Oluwafunmilola Kesa, Andrew Wang, Mihai Ilas, Patrick O'Hara, Oscar Giles, Neil Dhir, Mark Girolami, Theodoros Damoulas

Comput. J., January, 2024

2023

Optimal Observation-Intervention Trade-Off in Optimisation Problems with Causal Structure.

Kim Hammar, Neil Dhir

CoRR, 2023

Causal Entropy Optimization.

Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation.

Alex Andrew, Sam Spillard, Joshua Collyer, Neil Dhir

CoRR, 2022

2021

Chronological Causal Bandits.

Neil Dhir

CoRR, 2021

Prospective Artificial Intelligence Approaches for Active Cyber Defence.

Neil Dhir, Henrique Hoeltgebaum, Niall M. Adams, Mark Briers, Anthony Burke, Paul Jones

CoRR, 2021

Dynamic Causal Bayesian Optimization.

Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Near Real-Time Social Distancing in London.

James Walsh, Oluwafunmilola Kesa, Andrew Wang, Mihai Ilas, Patrick O'Hara, Oscar Giles, Neil Dhir, Theodoros Damoulas

CoRR, 2020

An Expectation-Based Network Scan Statistic for a COVID-19 Early Warning System.

Chance Haycock, Edward Thorpe-Woods, James Walsh, Patrick O'Hara, Oscar Giles, Neil Dhir, Theodoros Damoulas

CoRR, 2020

An Automatic Type-Inferential General Latent Feature Model.

Neil Dhir, Tomasz Rudny, Davide Zilli, Alessandra Tosi

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Identifying robust markers of Parkinson's disease in typing behaviour using a CNN-LSTM network.

Neil Dhir, Mathias Edman, Álvaro Sanchez Ferro, Tom Stafford, Colin J. Bannard

Proceedings of the 24th Conference on Computational Natural Language Learning, 2020

2019

Boltzmann Exploration Expectation-Maximisation.

Mathias Edman, Neil Dhir

CoRR, 2019

2018

Generalising Cost-Optimal Particle Filtering.

Andrew Warrington, Neil Dhir

CoRR, 2018

Coregionalised Locomotion Envelopes - A Qualitative Approach.

Neil Dhir, Houman Dallali, Mo Rastgaar

CoRR, 2018

Locomotion Envelopes for Adaptive Control of Powered Ankle Prostheses.

Neil Dhir, Houman Dallali, Evandro Maicon Ficanha, Guilherme Aramizo Ribeiro, Mo Rastgaar

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017

Interpreting Lion Behaviour as Probabilistic Programs.

Neil Dhir, Matthijs Vákár, Matthew Wijers, Andrew Markham, Frank D. Wood

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

2016

Nonparametric Bayesian models for unsupervised activity recognition and tracking.

Neil Dhir, Yura N. Perov, Frank D. Wood

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

2014

Improved activity recognition via Kalman smoothing and multiclass linear discriminant analysis.

Neil Dhir, Frank D. Wood

Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014