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Results: 57,944
Number of items: 57,944
  • Xian, Y., Lampert, C. H., Schiele, B., & Akata, Z. (2019). Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(9), 2251-2265. https://doi.org/10.1109/TPAMI.2018.2857768
  • Castiglione, F., Mancini, E., Pedicini, M., & Jarrah, A. S. (2019). Quantitative Modelling Approaches. In S. Ranganathan, M. Gribskov, K. Nakai, & C. Schönbach (Eds.), Encyclopedia of Bioinformatics and Computational Biology (Vol. 2, pp. 874-883). (Reference Module in Life Sciences). Elsevier. https://doi.org/10.1016/B978-0-12-809633-8.20454-8
  • Lucchini, M., Markoff, S., Crumley, P., Krauß, F., & Connors, R. M. T. (2019). Breaking degeneracy in jet dynamics: multi-epoch joint modelling of the BL Lac PKS 2155-304. Monthly Notices of the Royal Astronomical Society, 482(4), 4798-4812. https://doi.org/10.1093/mnras/sty2929
  • Robin, N., Marramà, G., Vonk, R., Kriwet, J., & Carnevale, G. (2019). Eocene isopods on electric rays: tracking ancient biological interactions from a complex fossil record. Palaeontology, 62(2), 287-303. https://doi.org/10.1111/pala.12398
  • Zhang, W., Mei, Y., Wu, P., Wu, H.-H., & He, M.-Y. (2019). Highly tunable periodic imidazole-based mesoporous polymers as cooperative catalysts for efficient carbon dioxide fixation. Catalysis Science & Technology, 9(4), 1030-1038. https://doi.org/10.1039/C8CY02595A
  • Oliehoek, F. A., Savani, R., Gallego, J., van der Pol, E., & Groß, R. (2019). Beyond Local Nash Equilibria for Adversarial Networks. In M. Atzmueller, & W. Duivesteijn (Eds.), Artificial Intelligence: 30th Benelux Conference, BNAIC 2018, ‘s-Hertogenbosch, The Netherlands, November 8–9, 2018 : revised selected papers (pp. 73-89). (Communications in Computer and Information Science; Vol. 121). Springer. https://doi.org/10.1007/978-3-030-31978-6_7
  • Moysiadis, G., Anagnostou, I., & Kandhai, D. (2019). Calibrating the Mean-Reversion Parameter in the Hull-White Model Using Neural Networks. In C. Alzate, & A. Monreale (Eds.), ECML PKDD 2018 Workshops: MIDAS 2018 and PAP 2018, Dublin, Ireland, September 10-14, 2018 : proceedings (pp. 23-36). (Lecture Notes in Computer Science; Vol. 11054), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-13463-1_2
  • Cole, D., & Barbolini, N. (2019). Marine flooding surfaces recorded in Permian black shales and coal deposits of the Main Karoo Basin (South Africa): Implications for basin dynamics and cross-basin correlation: Discussion. International journal of coal geology, 209, 130-131. https://doi.org/10.1016/j.coal.2018.04.013
  • Page, M., Licht, A., Dupont-Nivet, G., Meijer, N., Barbolini, N., Hoorn, C., Schauer, A., Huntington, K., Bajnai, D., Fiebig, J., Mulch, A., & Guo, Z. (2019). Synchronous cooling and decline in monsoonal rainfall in northeastern Tibet during the fall into the Oligocene icehouse. Geology, 47(3), 203-206. https://doi.org/10.1130/G45480.1
  • Kaya, M. Y., Dupont-Nivet, G., Proust, J. N., Roperch, P., Bougeois, L., Meijer, N., Frieling, J., Fioroni, C., Altıner, S. Ö., Vardar, E., Barbolini, N., Stoica, M., Aminov, J., Mamtimin, M., & Zhaojie, G. (2019). Palaeogene evolution and demise of the proto‐Paratethys Sea in Central Asia (Tarim and Tajik basins): Role of intensified tectonic activity at ca. 41 Ma. Basin Research, 31(3), 461-486. https://doi.org/10.1111/bre.12330
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