Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. 2018
  2. Development of the ASHRAE Global Thermal Comfort Database II

    Földváry, V., Cheung, T., Zhang, H., de Dear, R., Parkinson, T., Arens, E., Chun, C., Schiavon, S., Luo, M., Brager, G., Li, P., Kaam, S., Adebamowo, M. A., Andamon, M. M., Babich, F., Bouden, C., Bukovianska, H., Candido, C., Cao, B., Carlucci, S. & 44 othersCheong, D. K. W., Choi, J-H., Cook, M., Cropper, P., Deuble, M., Heidari, S., Indraganti, M., Jin, Q., Kim, H., Kim, J., Konis, K., Singh, M. K., Kwok, A., Lamberts, R., Loveday, D., Langevin, J., Manu, S., Moosmann, C., Nicol, F., Ooka, R., Oseland, N. A., Pagliano, L., Petráš, D., Rawal, R., Romero, R., Sekhar, C., Schweiker, M., Tartarini, F., Tanabe, S., Tham, K. W., Teli, D., Toftum, J., Toledo, L., Tsuzuki, K., De Vecchi, R., Wagner, A., Wang, Z., Wallbaum, H., Webb, L., Yang, L., Zhu, Y., Zhai, Y., Zhang, Y. & Zhou, X., Sep 2018, In : Building and Environment. 142, p. 502-512 11 p.

    Research output: Contribution to journalArticle

  3. Detecting repeated cancer evolution from multi-region tumor sequencing data

    Caravagna, G., Giarratano, Y., Ramazzotti, D., Tomlinson, I., Graham, T. A., Sanguinetti, G. & Sottoriva, A., 31 Aug 2018, In : Nature Methods. 15, p. 707-714 8 p.

    Research output: Contribution to journalArticle

  4. Autoregressive Point-Processes as Latent State-Space Models: a Moment-Closure Approach to Fluctuations and Autocorrelations

    Rule, M. & Sanguinetti, G., 27 Aug 2018, In : Neural Computation. 34 p.

    Research output: Contribution to journalArticle

  5. Flux-dependent graphs for metabolic networks

    Beguerisse-Díaz, M., Bosque, G., Oyarzún, D., Picó, J. & Barahona, M., 14 Aug 2018, In : npj Systems Biology and Applications. 4, 1, 14 p., 32.

    Research output: Contribution to journalArticle

  6. Regional Diversity in the Postsynaptic Proteome of the Mouse Brain

    Roy, M., Sorokina, O., McLean, C., Tapia-González, S., DeFelipe, J., Armstrong, J. D. & Grant, S., 1 Aug 2018, In : Proteomes. 6, 3, 18 p.

    Research output: Contribution to journalArticle

  7. A Survey of Machine Learning for Big Code and Naturalness

    Allamanis, M., Barr, E. T., Devanbu, P. & Sutton, C., 31 Jul 2018, In : ACM Computing Surveys. 51, 4, 36 p., 81.

    Research output: Contribution to journalArticle

  8. Data Diff: Interpretable, Executable Summaries of Changes in Distributions for Data Wrangling

    Sutton, C., Hobson, T., Geddes, J. & Caruana, R., 19 Jul 2018, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. London, United Kingdom: ACM, p. 2279-2288 10 p.

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

  9. HuD is a neural translation enhancer acting on mTORC1-responsive genes and counteracted by the Y3 small non-coding RNA

    Tebaldi, T., Zuccotti, P., Peroni, D., Köhn, M., Gasperini, L., Potrich, V., Bonazza, V., Dudnakova, T., Rossi, A., Sanguinetti, G., Conti, L., Macchi, P., D'Agostino, V., Viero, G., Tollervey, D., Hüttelmaier, S. & Quattrone, A., 19 Jul 2018, In : Molecular Cell. 71, 2, p. 256-270 26 p.

    Research output: Contribution to journalArticle

  10. BPRMeth: a flexible Bioconductor package for modelling methylation profiles

    Kapourani, C-A. & Sanguinetti, G., 15 Jul 2018, In : Bioinformatics. 34, 14, p. 2485-2486 2 p.

    Research output: Contribution to journalArticle

  11. Conditional Noise-Contrastive Estimation of Unnormalised Models

    Ceylan, C. & Gutmann, M., 15 Jul 2018, Proceedings of 35th International Conference on Machine Learning (ICML 2018). Dy, J. & Krause, A. (eds.). Stockholmsmässan, Stockholm Sweden: PMLR, Vol. 80. p. 725-733 9 p.

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

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