Items where Author is "Tino, P"

Journal article

KARLAFTIS, V.M., GIORGIO, J., VÉRTES, P.E., WANG, R., SHEN, Y., TINO, P., WELCHMAN, A. and KOURTZI, Z., 2019. Multimodal imaging of brain connectivity reveals predictors of individual decision strategy in statistical learning. Nature Human Behaviour, 3 (3), pp. 297-307. ISSN 2397-3374

GIORGIO, J., KARLAFTIS, V.M., WANG, R., SHEN, Y., TINO, P., WELCHMAN, A. and KOURTZI, Z., 2018. Functional brain networks for learning predictive statistics. Cortex, 107, pp. 204-219. ISSN 0010-9452

KARLAFTIS, V.M., WANG, R., SHEN, Y., TINO, P., WILLIAMS, G., WELCHMAN, A.E. and KOURTZI, Z., 2018. White-matter pathways for statistical learning of temporal structures. eNeuro, 5 (3): e0382. ISSN 2373-2822

WANG, R., SHEN, Y., TINO, P., WELCHMAN, A.E. and KOURTZI, Z., 2017. Learning predictive statistics from temporal sequences: dynamics and strategies. Journal of Vision, 17 (12), p. 1. ISSN 1534-7362

WANG, R., SHEN, Y., TINO, P., WELCHMAN, A.E. and KOURTZI, Z., 2017. Learning predictive statistics: strategies and brain mechanisms. The Journal of Neuroscience, 37 (35), pp. 8412-8427. ISSN 0270-6474

SHEN, Y., TINO, P. and TSANEVA-ATANASOVA, K., 2017. Classification framework for partially observed dynamical systems. Physical Review E, 95 (4): 043303. ISSN 2470-0045

ALAHMADI, H.H., SHEN, Y., FOUAD, S., LUFT, C.D.B., BENTHAM, P., KOURTZI, Z. and TINO, P., 2016. Classifying cognitive profiles using machine learning with privileged information in mild cognitive impairment. Frontiers in Computational Neuroscience, 10: 117. ISSN 1662-5188

BINNER, J., TINO, P., TEPPER, J., ANDERSEN, R., JONES, B. and KENDALL, G., 2010. Does money matter in inflation forecasting?. Physica A - Statistical Mechanics and its Applications, 389 (21), pp. 4793-4808.

Chapter in book

CHEN, X., SHEN, Y., ZAVALA, E., TSANEVA-ATANASOVA, K., UPTON, T., RUSSELL, G. and TINO, P., 2021. SOMiMS - topographic mapping in the model space. In: H. YIN, D. CAMACHO, P. TINO, R. ALLMENDINGER, A.J. TALLÓN-BALLESTEROS, K. TANG, S.-B. CHO, P. NOVAIS and S. NASCIMENTO, eds., Intelligent Data Engineering and Automated Learning – IDEAL 2021. 22nd International Conference, IDEAL 2021, Manchester, 25-27 November 2021, proceedings. Lecture notes in computer science (13113). Cham: Springer International Publishing, pp. 502-510. ISBN 9783030916077

BINNER, J., JONES, B., KENDALL, G., TEPPER, J. and TINO, P., 2006. Does money matter? An artificial intelligence approach. In: Proceedings of the 9th Joint Conference on Information Sciences (JCIS-2006). UNSPECIFIED. ISBN 9078677015