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Results: 111
Number of items: 111
  • Open Access
    O'Connor, P., Gavves, E., & Welling, M. (2019). Initialized Equilibrium Propagation for Backprop-Free Training. In ICLR 2019: International Conference on Learning Representations : New Orleans, Louisiana, United States, May 6-May 9, 2019 OpenReview. https://openreview.net/forum?id=B1GMDsR5tm
  • Open Access
    Chen, Y., Mensink, T., & Gavves, E. (2019). 3D Neighborhood Convolution: Learning Depth-Aware Features for RGB-D and RGB Semantic Segmentation. In 2019 International Conference on 3D Vision: 3DV 2019 : proceedings : Quebec, Canada, 15-18 September 2019 (pp. 173-182). IEEE Computer Society, Conference Publishing Services. https://doi.org/10.48550/arXiv.1910.01460, https://doi.org/10.1109/3DV.2019.00028
  • Open Access
    Gupta, D. K., de Bruijn, N., Panteli, A., & Gavves, E. (2019). Tracking-Assisted Segmentation of Biological Cells. Paper presented at Medical Imaging meets NeurIPS workshop 2019, Vancouver, British Columbia, Canada.
  • Open Access
    van der Heiden, T., Nagaraja, N. S., Weiß, C., & Gavves, E. (2019). SafeCritic: Collision-Aware Trajectory Prediction. ArXiv. https://doi.org/10.48550/arXiv.1910.06673
  • Open Access
    Liao, S., Gavves, E., & Snoek, C. G. M. (2019). Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : 16-20 June 2019, Long Beach, California (pp. 9751-9759). (CVPR). IEEE Computer Society. https://doi.org/10.48550/arXiv.1904.05404, https://doi.org/10.1109/CVPR.2019.00999
  • Open Access
    Hussein, N., Gavves, E., & Smeulders, A. W. M. (2019). VideoGraph: Recognizing Minutes-Long Human Activities in Videos. Paper presented at 1st Workshop on Graph Based Learning in Computer Vision, Seoul, Korea, Republic of. https://arxiv.org/abs/1905.05143
  • Open Access
    O'Connor, P., Gavves, E., & Welling, M. (2019). Training a Spiking Neural Network with Equilibrium Propagation. Proceedings of Machine Learning Research, 89, 1516-1523. http://proceedings.mlr.press/v89/o-connor19a.html
  • Open Access
    Louizos, C., Reisser, M., Blankevoort, T., Gavves, E., & Welling, M. (2019). Relaxed Quantization for Discretized Neural Networks. In ICLR 2019: International Conference on Learning Representations : New Orleans, Louisiana, United States, May 6-May 9, 2019 OpenReview. https://openreview.net/forum?id=HkxjYoCqKX
  • Open Access
    Davidson, T. R., Tomczak, J. M., & Gavves, E. (2019). Increasing Expressivity of a Hyperspherical VAE. Paper presented at Bayesian Deep Learning Workshop, Vancouver, British Columbia, Canada. https://doi.org/10.48550/arXiv.1910.02912
  • Valmadre, J., Bertinetto, L., Henriques, J. F., Tao, R., Vedaldi, A., Smeulders, A. W. M., Torr, P. H. S., & Gavves, E. (2018). Long-Term Tracking in the Wild: A Benchmark. In V. Ferrari, M. Hebert, C. Sminchisescu, & Y. Weiss (Eds.), Computer Vision – ECCV 2018: 15th European Conference, Munich, Germany, September 8-14, 2018: proceedings (Vol. III, pp. 692-707). (Lecture Notes in Computer Science; Vol. 11207). Springer. https://doi.org/10.1007/978-3-030-01219-9_41
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