Institute for Adaptive and Neural Computation

2021

Handwritten digits recognition using dictionary learning

Abolghasemi, V., Ameri, R. & Nazarpour, K., 1 Oct 2021, Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches: Fundamentals, technologies and applications. Institution of Engineering and Technology, p. 83-116 34 p.

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

Stimulus interaction in transcutaneous electrical stimulation

Dupan, S., Jabban, L., Metcalfe, B. W. & Nazarpour, K., 23 Jul 2021, Somatosensory Feedback for Neuroprosthetics. Guclu, B. (ed.). 1 ed. Elsevier, p. 151-175 25 p.

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

Deep Learning for Device-free Human Activity Recognition Using WiFi Signals

Guo, L., Zhang, H., Guo, W., Fang, J., Lu, B., Ma, E., Li, G., Lin, C. & Wang, L., 26 Apr 2021, Generalization with Deep Learning For Improvement on Sensing Capability. Chen, Z., Wu, M. & Li, X. (eds.). Singapore: World Scientific, p. 101-137 38 p.

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

Prediction of Cellular Burden with Host--Circuit Models

Nikolados, E-M., Weiße, A. Y. & Oyarzún, D. A., 7 Jan 2021, Synthetic Gene Circuits : Methods and Protocols. Menolascina, F. (ed.). New York, NY: Springer US, p. 267-291 25 p. (Methods in Molecular Biology; vol. 2229).

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

Open Access

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2020

Leadership and Maturity: How Do They Affect Learning Analytics Adoption in Latin America?

Hilliger, I., Pérez-Sanagustín, M., Pérez-Álvarez, R., Henríquez, V., Guerra, J., Zuñiga-Prieto, M. Á., Ortiz-Rojas, M., Tsai, Y-S., Gasevic, D., Muñoz-Merino, P. J., Broos, T. & De Laet, T., 11 Aug 2020, (E-pub ahead of print) Adoption of Data Analytics in Higher Education Learning and Teaching. Ifenthaler, D. & Gibson, D. (eds.). Cham: Springer International Publishing AG, p. 305-326 22 p.

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

Single Color Sketch-Based Image Retrieval in HSV Color Space

Xia, Y., Wang, S., Li, Y., You, L., Yang, X. & Zhang, J. J., 14 Jul 2020, Transactions on Computational Science XXXVII: Special Issue on Computer Graphics. Gavrilova, M. L., Tan, C. J. K., Chang, J. & Thalmann, N. M. (eds.). Berlin, Heidelberg: Springer Berlin Heidelberg, p. 77-90 14 p. (Lecture Notes in Computer Science; vol. 12230).

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

Heart Cells are aMAZEing

Kudryashova, N. & Panfilov, A., 17 Apr 2020, The Art of Theoretical Biology. Matthäus, F., Matthäus, S., Harris, S. & Hillen, T. (eds.). Cham: Springer International Publishing, p. 138-139 2 p.

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

Lost in the Cells

Kudryashova, N. & Panfilov, A., 17 Apr 2020, The Art of Theoretical Biology. Matthäus, F., Matthäus, S., Harris, S. & Hillen, T. (eds.). Cham: Springer International Publishing, p. 78-79 2 p.

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

2019

Scaling Spike Detection and Sorting for Next-Generation Electrophysiology

Hennig, M. H., Hurwitz, C. & Sorbaro, M., 10 May 2019, In Vitro Neuronal Networks: From Culturing Methods to Neuro-Technological Applications. Springer New York LLC, p. 171-184 14 p. (Advances in Neurobiology; vol. 22).

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

EXOTica: An Extensible Optimization Toolset for Prototyping and Benchmarking Motion Planning and Control

Ivan, V., Yang, Y., Merkt, W., Camilleri, M. P. & Vijayakumar, S., 2019, Robot Operating System (ROS): The Complete Reference (Volume 3). Koubaa, A. (ed.). Cham: Springer International Publishing, p. 211-240 30 p. (Studies in Computational Intelligence ; vol. 778).

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

Gene Regulatory Network Inference: An Introductory Survey

Huynh-Thu, V. A. & Sanguinetti, G., 2019, Gene Regulatory Networks: Methods and Protocols. Sanguinetti, G. & Huynh-Thu, V. A. (eds.). New York, NY: Springer New York LLC, p. 1-23 23 p.

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

RKappa: Software for Analyzing Rule-Based Models

Sorokin, A., Sorokina, O. & Douglas Armstrong, J., 2019, Modeling Biomolecular Site Dynamics: Methods and Protocols. Hlavacek, W. S. (ed.). New York, NY: Springer New York LLC, p. 363-390 28 p.

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

Tree-Based Learning of Regulatory Network Topologies and Dynamics with Jump3

Huynh-Thu, V. A. & Sanguinetti, G., 2019, Gene Regulatory Networks: Methods and Protocols. Sanguinetti, G. & Huynh-Thu, V. A. (eds.). New York, NY: Springer New York LLC, p. 217-233 17 p.

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

Using BRIE to Detect and Analyze Splicing Isoforms in scRNA-Seq Data

Huang, Y. & Sanguinetti, G., 2019, Computational Methods for Single-Cell Data Analysis. Yuan, G-C. (ed.). New York, NY: Springer New York LLC, p. 175-185 11 p. (Methods in Molecular Biology; vol. 1935).

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

2016

Neural Maps: Their Function and Development

Bednar, J. & Williams, C. K. I., Nov 2016, From Neuron to Cognition via Computational > Neuroscience. Arbib, M. & Bonaiuto, J. (eds.). MIT Press, p. 409-432 34 p.

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

Detecting Artifactual Events in Vital Signs Monitoring Data

Lal, P., Williams, C. K. I., Georgatzis, K., Hawthorne, C., McMonagle, P., Piper, I. & Shaw, M., Oct 2016, Machine Learning for Healthcare Technologies. Clifton, D. A. (ed.). IET, p. 7-32 26 p.

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

2015

Probabilistic Inference and Bayesian Priors in Visual Perception

Sotiropoulos, G. & Series, P., 2 Nov 2015, Biologically Inspired Computer Vision: Fundamentals and Applications. Wiley-VCH Verlag GmbH & Co. KGaA, p. 201-220 20 p.

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

Le cerveau est-il une machine Bayésienne

Translated title of the contribution: Is the brain a machine BayesianSeries, P., 2015, (Accepted/In press) Les méthodes bayésiennes, sciences et épistémologie. Drouet, I. (ed.). 16 p.

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

The LuminUs: Providing Musicians with Visual Feedback on the Gaze and Body Motion of Their Co-performers

Morgan, E., Gunes, H. & Bryan-Kinns, N., 2015, Human-Computer Interaction – INTERACT 2015: 15th IFIP TC 13 International Conference, Bamberg, Germany, September 14-18, 2015, Proceedings, Part II. Abascal, J., Barbosa, S., Fetter, M., Gross, T., Palanque, P. & Winckler, M. (eds.). Cham: Springer International Publishing, p. 47-54 8 p. (Lecture Notes in Computer Science; vol. 9297).

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

Open Access

File

2014

From intelligent machines to the human brain

Series, P. & Sprevak, M., 30 Sept 2014, Philosophy and the Sciences for Everyone. Massimi, M. (ed.). Routledge, p. 86-102 17 p.

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

Chapter Two - Towards a Systems Level Understanding of the Oxygen Response of Escherichia coli

Bettenbrock, K., Bai, H., Ederer, M., Green, J., Hellingwerf, K. J., Holcombe, M., Kunz, S., Rolfe, M. D., Sanguinetti, G., Sawodny, O., Sharma, P., Steinsiek, S. & Poole, R. K., 2014, Advances in Microbial Systems Biology. Vol. 64. p. 65 - 114 50 p.

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

Model Reduction of Genetic-Metabolic Networks via Time Scale Separation

Kuntz, J., Oyarzún, D. & Stan, G-B., 2014, A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and System Characterizations. Kulkarni, V. V., Stan, G-B. & Raman, K. (eds.). Dordrecht: Springer Netherlands, p. 181-210 30 p.

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

2012

Evolution of the Cognitive Proteome: From Static to Dynamic Network Models

Armstrong, J. D. & Sorokina, O., 2012, Advances in Systems Biology. Goryanin, I. I. & Goryachev, A. B. (eds.). Springer New York, p. 119-134 16 p. (Advances in Experimental Medicine and Biology; vol. 736).

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

2011

Expectation-Maximization Methods for Solving (PO)MDPs and Optimal Control Problems.

Toussaint, M., Storkey, A. J. & Harmeling, S., 2011, Bayesian Time Series Models. Chiappa, S. & Barber, D. (eds.). Cambridge University Press, p. 388-413 26 p.

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

Some issues in computational modelling: Occam’s Razor and Hegel’s hair gel

Shillcock, R., Roberts, M., Kreiner, H. & Obregon-Sargent, M., 2011, Connectionist Models of Neurocognition and Emergent Behaviour. Davelaar, E. (ed.). Singapore: World Scientific Press, p. 343-355 13 p.

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

2010

Sparse instrumental variables (SPIV) for genome-wide studies

Agakov, F. V., McKeigue, P., Krohn, J. & Storkey, A., 1 Jan 2010, Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, NIPS 2010. p. 28-36

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

Mixture Model on Graphs: A Probabilistic Model for Network-Based Analysis of Proteomic Data

Noirel, J., Sanguinetti, G. & Wright, P., 2010, Systems Biology for Signaling Networks: Part II. Choi, S. (ed.). Springer New York, p. 371-397 27 p. (Systems Biology).

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

Optimal Well Placement: Paper B003

Farmer, C., Fowkes, J. & Gould, N., 2010, Proceedings of the 12th European Conference on the Mathematics of Oil Recovery, Oxford.

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

2009

Misleading Learners: Co-opting Your Spam Filter

Nelson, B., Barreno, M., Jack Chi, F., Joseph, A. D., Rubinstein, B. I. P., Saini, U., Sutton, C., Tygar, J. D. & Xia, K., 2009, Machine Learning in Cyber Trust: Security, Privacy, and Reliability. Springer US, p. 17-51 35 p.

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

2008

When Training and Test Sets Are Different: Characterizing Learning Transfer

Storkey, A., Quiñonero-Candela, J., Sugiyama, M., Schwaighofer, A. & Lawrence, ND., Dec 2008, Dataset Shift in Machine Learning. Cambridge: Yale University Press in association with the Museum of London, p. 3-28 26 p. (Neural Information Processing Series).

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

2007

Approximation methods for gaussian process regression

Quiñonero-Candela, J., Rasmussen, C. E. & Williams, C. K. I., Aug 2007, Large-Scale Kernel Machines. Bottou, L., Chapelle, O., DeCoste, D. & Weston, J. (eds.). MIT Press, 24 p.

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

2006

Dataset Issues in Object Recognition

Ponce, J., Berg, T. L., Everingham, M., Forsyth, D. A., Hebert, M., Lazebnik, S., Marszalek, M., Schmid, C., Russell, B. C., Torralba, A., Williams, C. K. I., Zhang, J. & Zisserman, A., 2006, Toward Category-Level Object Recognition. Ponce, J., Hebert, M., Schmid, C. & Zisserman, A. (eds.). Springer Berlin Heidelberg, p. 29-48 20 p. (Lecture Notes in Computer Science; vol. 4170).

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

Identifying Submodules of Cellular Regulatory Networks

Sanguinetti, G., Rattray, M. & Lawrence, N. D., 2006, Computational Methods in Systems Biology. Priami, C. (ed.). Springer Berlin Heidelberg, p. 155-168 14 p. (Lecture Notes in Computer Science; vol. 4210).

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

Sequential Learning of Layered Models from Video

Titsias, M. K. & Williams, C. K. I., 2006, Toward Category-Level Object Recognition. Ponce, J., Hebert, M., Schmid, C. & Zisserman, A. (eds.). Springer Berlin Heidelberg, Vol. V. p. 577-595 19 p. (Lecture Notes in Computer Science; vol. 4170).

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

Studying neuronal function using the Drosophila genetic system

Armstrong, D. & Goodwin, S. F., 2006, Molecular Biology of the Neuron. p. 1-14 15 p.

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

2005

Covariance Functions

Rasmussen, C. E. & Williams, C. K. I., Nov 2005, Gaussian Processes for Machine Learning. Rasmussen, C. E. & Williams, C. K. I. (eds.). MIT Press, p. 79-102 24 p. (Adaptive Computation and Machine Learning series).

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

Open Access

Model Selection and Adaptation of Hyperparameters

Rasmussen, C. E. & Williams, C. K. I., Nov 2005, Gaussian Processes for Machine Learning. Rasmussen, C. E. & Williams, C. K. I. (eds.). MIT Press, p. 105-128 24 p. (Adaptive Computation and Machine Learning series).

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

Open Access

2000

Functional magnetic resonance imaging dataset analysis

Goddard, N. H., Hood, G., Cohen, J. D., Nystrom, L. E., Eddy, W. F., Genovese, C. R. & Noll, D. C., 2000, Industrial strength parallel computing. Koniges, A. E. (ed.). Morgan Kaufman, p. 431-452 23 p.

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

1999

Latent Variable Models

Bishop, C. M., 1 Jan 1999, Learning in Graphical Models. Jordan, M. I. (ed.). MIT Press, p. 371–403 33 p. (Adaptive Computation and Machine Learning).

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

A novel approach to Drosophila neurophysiology: the targeted expression of aequorin

Rosay, P., Kaiser, K. & Armstrong, J. D., 1999, Handbook of Molecular-Genetic Techniques for Brain and Behavior Research. Crusio, W. E. & Gerlai, R. T. (eds.). Elsevier, p. 487-495 9 p. (Techniques in the Behavioral and Neural Sciences).

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

1998

Noise Removal by Nonlinear Synapses

Van Rossum, M. C. W. & Smith, R. G., 1998, Computational Neuroscience: Trends in Research, 1998. Bower, J. M. (ed.). Boston, MA: Springer US, p. 297-302 6 p.

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

1997

An Upper Bound on the Bayesian Error Bars for Generalized Linear Regression

Qazaz, C. S., Williams, C. K. I. & Bishop, C. M., 1997, Mathematics of Neural Networks: Models, Algorithms and Applications. Norwell, MA, USA: Springer US, p. 295-299 5 p. (Operations Research/Computer Science Interfaces Series; vol. 8).

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

Modelling Conditional Probability Distributions for Periodic Variables

Bishop, C. & Nabney, I., 1997, Mathematics of Neural Networks: Models, Algorithms and Applications. Ellacott, S., Mason, J. & Anderson, I. (eds.). Springer US, p. 118-122 5 p. (Operations Research/Computer Science Interfaces Series; vol. 8).

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

Prediction With Gaussian Processes: From Linear Regression To Linear Prediction And Beyond

Williams, C., 1997, Learning in Graphical Models. p. 599-621 23 p. (NATO ASI Series D: Behavioural and Social Sciences; vol. 89).

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

The GENESIS Simulator-based Neuronal Database

Beeman, D., Bower, J. M., Schutter, E. D., Efthimiadis, E. N., Goddard, N. & Leigh, J., 1997, Progress in Neuroinformatics. Koslow, S. & Huerta, M. (eds.). Lawrence Erlbaum Associates, Vol. 1. 203 p.

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

Open Access

1996

Handbook of Neural Computation

Bishop, C. M., 1996, Handbook of Neural Computation. Oxford University Press

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

1995

1990

Lexical Hypotheses in Continuous Speech

Shillcock, R., 1990, Cognitive models of speech processing. Altmann, G. T. M. (ed.). MIT Press, p. 24 - 49 26 p.

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

Institute for Adaptive and Neural Computation

Research output

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