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Results: 114
Number of items: 114
  • Open Access
    Pervez, A., & Gavves, E. (2021). Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders. Proceedings of Machine Learning Research, 139, 8536-8545. https://proceedings.mlr.press/v139/pervez21a.html
  • Open Access
    Liao, S. (2021). Deep learning with 3D and label geometry. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Gavves, E., Tao, R., Gupta, D. K., & Smeulders, A. W. M. (2021). Model Decay in Long-Term Tracking. In Proceedings of ICPR 2020: 25th International Conference on Pattern Recognition : Milan, 10-15 January 2021 (pp. 2685-2692). IEEE. https://doi.org/10.1109/ICPR48806.2021.9412648
  • Open Access
    Chen, Y., Hu, V. T., Gavves, E., Mensink, T., Mettes, P., Yang, P., & Snoek, C. G. M. (2020). PointMixup: Augmentation for Point Clouds. In A. Vedaldi, H. Bischof, T. Brox, & J. M. Frahm (Eds.), Computer Vision – ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020 : proceedings (Vol. III, pp. 330-345). (Lecture Notes in Computer Science; Vol. 12348). Springer. https://doi.org/10.1007/978-3-030-58580-8_20
  • Open Access
    Pervez, A., Cohen, T., & Gavves, E. (2020). Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks. Proceedings of Machine Learning Research, 119, 7632-7640. http://proceedings.mlr.press/v119/pervez20a.html
  • Open Access
    O'Connor, P. (2020). Biologically plausible deep learning: Should airplanes flap their wings? [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    van de Leur, R. R., Blom, L. J., Gavves, E., Hof, I. E., van der Heijden, J. F., Clappers, N. C., Doevendans, P. A., Hassink, R. J., & van Es, R. (2020). Automatic Triage of 12‐Lead ECGs Using Deep Convolutional Neural Networks. Journal of the American Heart Association, 9(10). https://doi.org/10.1161/JAHA.119.015138
  • Open Access
    Oh, C., Tomczak, J. M., Gavves, E., & Welling, M. (2020). Combinatorial Bayesian Optimization using the Graph Cartesian Product. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, & R. Garnett (Eds.), 32nd Conference on Neural Information Processing Systems (NeurIPS 2019): Vancouver, Canada, 8-14 December 2019 (Vol. 4, pp. 2891-2901). (Advances in Neural Information Processing Systems; Vol. 32). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2019/hash/2cb6b10338a7fc4117a80da24b582060-Abstract.html
  • Open Access
    Panteli, A., Gupta, D. K., de Bruijn, N., & Gavves, E. (2020). Siamese Tracking of Cell Behaviour Patterns. Proceedings of Machine Learning Research, 121, 570-587. http://proceedings.mlr.press/v121/panteli20a.html
  • Kristan, M., Matas, J., Leonardis, A., Felsberg, M., Pflugfelder, R., Kämäräinen, J.-K., Čehovin Zajc, L., Drbohlav, O., Lukežič, A., Berg, A., Eldesokey, A., Käpylä, J., Fernández, G., Gonzalez-Garcia, A., Memarmoghadam, A., Lu, A., He, A., Varfolomieiev, A., Chan, A., ... Ni, Z. (2019). The Seventh Visual Object Tracking VOT2019 Challenge Results. In 2019 International Conference on Computer Vision, Workshops: proceedings : 27 October-2 November 2019, Seoul, Korea (pp. 2206-2241). IEEE Computer Society. https://doi.org/10.1109/ICCVW.2019.00276
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