Institute for Adaptive and Neural Computation

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  • 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, p. 267-291 25 p. (Methods in Molecular Biology; vol. 2229).

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

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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., 12 Aug 2020, Adoption of Data Analytics in Higher Education Learning and Teaching. Ifenthaler, D. & Gibson, D. (eds.). 1 ed. Cham: Springer, p. 305-326 22 p. (Advances in Analytics for Learning and Teaching).

    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, 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, 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, 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, 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, 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, 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, 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, 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, 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, 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, p. 47-54 8 p. (Lecture Notes in Computer Science; vol. 9297).

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

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  • 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, 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, 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.). World Scientific, 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, 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, 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, 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, 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, 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, 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, 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, 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, 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

    Bottom-up connectionist modelling of speech

    Cairns, P., Shillcock, R., Chater, N. & Levy, J., 20 Dec 1995, Preview this Book Connectionist Models Of Memory And Language. Levy, J. (ed.). CRC Press, 289 p.

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

  • Multiphase flow monitoring in oil pipelines

    Bishop, C. M., 1995, Applications of Neural Networks: Section B. Murray, A. (ed.). Springer, p. 133-155 23 p.

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

  • Regression with Gaussian processes

    Williams, C. K. I., 1995, Mathematics of Neural Networks: Models, Algorithms and Applications. Springer, p. 378-382 5 p. (Operations Research/Computer Science Interfaces Series; vol. 8).

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

  • 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