Peter Tino

Colleges, School and Institutes

Willingness to take PhD students

Yes

PhD projects

Peter Tino’s research interests include:

Neural network architectures for processing sequential and otherwise structured data
Dynamical systems
Fractal theory
Spiking neuron networks
Statistical pattern analysis - in particular, probabilistic latent space modelling
Visualisation of high-dimensional and structured data
Computational finance

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Most downloaded publications

Shining a Light on Awareness: A Review of Functional Near-Infrared Spectroscopy for Prolonged Disorders of Consciousness
Hamid Dehghani, Sam Lucas, Peter Tino & Damian Cruse, 22 May 2018, In: Frontiers in neurology. 9, 350.

Research output: Contribution to journal › Article › peer-review

173 downloads
Ordinal regression neural networks based on concentric hyperspheres
Peter Tino, Nov 2014, In: Neural Networks. 59, p. 51-60

Research output: Contribution to journal › Article › peer-review

159 downloads
Model-free causality detection: An application to social media and financial data
Mirco Musolesi & Peter Tino, 4 May 2017, (E-pub ahead of print) In: Physica A: Statistical Mechanics and its Applications.

Research output: Contribution to journal › Article › peer-review

115 downloads
Learning pharmacokinetic models for in vivo glucocorticoid activation
Kerstin Bunte, David Smith, Zaki Hassan-Smith, Wiebke Arlt & Peter Tino, 14 Oct 2018, In: Journal of Theoretical Biology. 455, p. 222-231

Research output: Contribution to journal › Article › peer-review

102 downloads
Asymptotic Fisher Memory of Randomized Linear Symmetric Echo State Networks
Peter Tino, 12 Jul 2018, In: Neurocomputing. 298, p. 4-8 16 p.

Research output: Contribution to journal › Article › peer-review

89 downloads

Recent publications

A predictable conserved DNA base composition signature defines human core DNA replication origins
Ildem Akerman, Alina Bazarova, Romain Derelle, Peter Tino, Dec 2020, In: Nature Communications. 11, 1, 15 p., 4826 .

Research output: Contribution to journal › Article › peer-review

Representing experience in continuous evolutionary optimisation through problem-tailored search operators
Stephen Friess, Peter Tino, 3 Sep 2020, 2020 IEEE Congress on Evolutionary Computation (CEC). IEEE, p. 1-7

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Improving sampling in evolution strategies through mixture-based distributions built from past problem instances
Stephen Friess, Peter Tino & Xin Yao, 31 Aug 2020, Parallel Problem Solving from Nature – PPSN XVI. Springer, p. 583-596 14 p. (Lecture Notes in Computer Science; vol. 12269).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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