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Results: 24
Number of items: 24
  • Open Access
    Davidson, T. R., Falorsi, L., De Cao, N., Kipf, T., & Tomczak, J. M. (2018). Hyperspherical Variational Auto-Encoders. In A. Globerson, & R. Silva (Eds.), Uncertainty in Artificial Intelligence: proceedings of the Thirty-Fourth Concerence (2018) : August 6-10, 2018, Monterey, California, USA (pp. 856-865). AUAI Press. http://auai.org/uai2018/proceedings/papers/309.pdf
  • Open Access
    Hasenclever, L., Tomczak, J. M., van den Berg, R., & Welling, M. (2017). Variational Inference with Orthogonal Normalizing Flows. Paper presented at Bayesian Deep Learning Workshop NIPS 2017, Long Beach, United States. http://bayesiandeeplearning.org/2017/papers/51.pdf
  • Open Access
    Tomczak, J. M., Ilse, M., & Welling, M. (2017). Deep Learning with Order-invariant Operator for Multi-instance Histopathology Classification. Abstract from Medical Imaging meets NIPS Workshop NIPS 2017, Long Beach, United States. https://doi.org/10.48550/arXiv.1712.00310
  • Open Access
    Tomczak, J. M., & Welling, M. (2016). Improving Variational Auto-Encoders using Householder Flow. Paper presented at Bayesian Deep Learning Workshop NIPS 2016, Barcelona, Spain. https://arxiv.org/abs/1611.09630
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