Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. 2019
  2. 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 proceedingChapter

  3. 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 proceedingChapter

  4. 2018
  5. Context Embedding Networks

    Kim, K. H., Mac Aodha, O. & Perona, P., 17 Dec 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers (IEEE), p. 8679-8687 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  6. Teaching Categories to Human Learners with Visual Explanations

    Mac Aodha, O., Su, S., Chen, Y., Perona, P. & Yue, Y., 17 Dec 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers (IEEE), p. 3820-3828 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  7. The iNaturalist Species Classification and Detection Dataset

    Van Horn, G., Mac Aodha, O., Song, Y., Cui, Y., Sun, C., Shepard, A., Adam, H., Perona, P. & Belongie, S., 17 Dec 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers (IEEE), p. 8769-8778 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  8. Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

    Turner, J., Cano Reyes, J., Radu, V., Crowley, E., O'Boyle, M. & Storkey, A., 13 Dec 2018, Proceedings of the - Workload Characterization (IISWC), 2018 IEEE International Symposium on. Raleigh, North Carolina, USA: Institute of Electrical and Electronics Engineers (IEEE), p. 101-110 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  9. The SHEILA framework: informing institutional strategies and policy processes of learning analytics

    Tsai, Y-S., Moreno-Marcos, P. M., Jivet, I., Scheffel, M., Tammets, K., Kollom, K. & Gasevic, D., 11 Dec 2018, In : Journal of Learning Analytics. 5, 3, p. 5-20 16 p.

    Research output: Contribution to journalArticle

  10. Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners

    Chen, Y., Singla, A., Mac Aodha, O., Perona, P. & Yue, Y., 8 Dec 2018, Advances in Neural Information Processing Systems 31. Bengio, S., Wallach, H., Larochelle, H., Grauman, K., Cesa-Bianchi, N. & Garnett, R. (eds.). Neural Information Processing Systems, Vol. 31. p. 1476-1486 11 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  11. Non-parametric Physiological Classification of Retinal Ganglion Cells in the Mouse Retina

    Jouty, J., Hilgen, G., Sernagor, E. & Hennig, M. H., 7 Dec 2018, In : Frontiers in Cellular Neuroscience. 12, 14 p., 481.

    Research output: Contribution to journalArticle

  12. SHEILA: Supporting Higher Education to Intergrate Learning Analytics Research Report

    Tsai, Y-S., Gasevic, D., Whitelock-Wainwright, A., Muñoz-Merino, P. J., Moreno-Marcos, P. M., Rubio Fernández, A., Delgado Kloos, C., Scheffel, M., Jivet, I., Drachsler, H., Tammets, K., Calleja, A. R., Kollom, K., Haywood, J., Cantero, N., Gourdin, A., Kelo, M. & Benke-Åberg, R., 30 Nov 2018, Edinburgh, UK: The University of Edinburgh. 44 p.

    Research output: Book/ReportOther report

  13. Mirror Neurons, Prediction and Hemispheric Coordination; The Prioritizing of Intersubjectivity over 'Intrasubjectivity'

    Shillcock, R., Thomas, J. & Bailes, R., 24 Nov 2018, In : Axiomathes. p. 1-15 15 p.

    Research output: Contribution to journalArticle

  14. Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting

    Bekasovs, A. & Murray, I., 16 Nov 2018, (Accepted/In press) p. 1-6. 6 p.

    Research output: Contribution to conferencePaper

  15. Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria

    Järvenpää, M., Gutmann, M., Vehtari, A. & Marttinen, P., 13 Nov 2018, In : Annals of Applied Statistics. 12, 4, p. 2228-2251 24 p.

    Research output: Contribution to journalArticle

  16. Co-Designing a Device for Behaviour-Based Energy Reduction in a Large Organisation

    Morgan, E., Webb, L., Carter, C. & Goddard, N., Nov 2018, In : Proceedings of the ACM on Human-Computer Interaction. 2, CSCW, p. 125:1-125:23 23 p., 125.

    Research output: Contribution to journalArticle

  17. Geppetto: a reusable modular open platform for exploring neuroscience data and models

    Cantarelli, M., Marin, B., Quintana, A., Earnshaw, M., Court, R., Gleeson, P., Dura-bernal, S., Silver, R. A. & Idili, G., 19 Oct 2018, In : Philosophical Transactions of the Royal Society B: Biological Sciences. 373, 1758, p. 1-13 13 p.

    Research output: Contribution to journalArticle

  18. Information Estimation Using Non-Parametric Copulas

    Safaai, H., Onken, A., Harvey, C. & Panzeri, S., 10 Oct 2018, (Accepted/In press) In : Physical Review E. 17 p.

    Research output: Contribution to journalArticle

  19. Is there a burden attached to synaesthesia? Health screening of synaesthetes in the general population

    Carmichael, D., Smees, R., Shillcock, R. C. & Simner, J., 3 Oct 2018, In : British Journal of Psychology. p. 1-19 19 p.

    Research output: Contribution to journalArticle

  20. Dynamic Evaluation of Neural Sequence Models

    Krause, B., Mbabazi, E., Murray, I. & Renals, S., 1 Oct 2018, Proceedings of the 35th International Conference on Machine Learning. Dy, J. & Krause, A. (eds.). Stockholmsmässan, Stockholm Sweden: PMLR, Vol. 80. p. 2766-2775 10 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  21. Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio

    Jastrzębski, S., Kenton, Z., Arpit, D., Ballas, N., Fischer, A., Bengio, Y. & Storkey, A., Oct 2018, Proceedings of 27th International Conference on Artificial Neural Networks. Rhodes, Greece: Springer, Cham, p. 392-402 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  22. Augmenting Image Classifiers Using Data Augmentation Generative Adversarial Networks

    Antoniou, A., Storkey, A. & Edwards, H., 27 Sep 2018, Artificial Neural Networks and Machine Learning – ICANN 2018. Rhodes, Greece, p. 594-603 10 p. (Lecture Notes in Computer Science; vol. 11141).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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