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Results: 160
Number of items: 160
  • Open Access
    Kipf, T. N., & Welling, M. (2016). Variational Graph Auto-Encoders. Paper presented at Bayesian Deep Learning Workshop NIPS 2016, Barcelona, Spain. https://doi.org/10.48550/arXiv.1611.07308
  • Open Access
    Roijers, D. M. (2016). Multi-objective decision-theoretic planning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Park, M., Foulds, J., Chaudhuri, K., & Welling, M. (2016). Private Topic Modeling. In Private Multi-Party Machine Learning: NIPS 2016 workshop : Barcelona, December 9 : PMPML'16 NIPS. https://arxiv.org/abs/1609.04120
  • Open Access
    Louizos, C., Swersky, K., Li, Y., Welling, M., & Zemel, R. (2016). The Variational Fair Autoencoder. In ICLR 2016: International Conference on Learning Representations: May 2-4, 2016, San Juan, Puerto Rico. Accepted papers (Conference Track) Computational and Biological Learning Society. https://arxiv.org/abs/1511.00830
  • Open Access
    Korattikara, A., Chen, Y., & Welling, M. (2016). Sequential Tests for Large Scale Learning. Neural Computation, 28(1), 45-70. https://doi.org/10.1162/NECO_a_00226
  • Meeds, E., Leenders, R., & Welling, M. (2015). Hamiltonian ABC. In M. Meila, & T. Heskes (Eds.), Uncertainty in Artificial Intelligence: proceedings of the thirty-first conference (2015): July 12-16, Amsterdam, Netherlands (pp. 582-591). AUAI Press. http://auai.org/uai2015/proceedings/papers/266.pdf
  • Kingma, D. P., Rezende, D. J., Mohamed, S., & Welling, M. (2015). Semi-supervised Learning with Deep Generative Models. In Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, & K. Q. Weinberger (Eds.), 28th Annual Conference on Neural Information Processing Systems 2014: December 8-13, 2014, Montreal, Canada (Vol. 4, pp. 3581-3589). (Advances in Neural Information Processing Systems; Vol. 27). Curran. http://papers.nips.cc/paper/5352-semi-supervised-learning-with-deep-generative-models
  • Open Access
    Korattikara, A., Rathod, V., Murphy, K., & Welling, M. (2015). Bayesian Dark Knowledge. In C. Cortes, N. D. Lawrence, D. D. Lee, M. Sugiyama, & R. Garnett (Eds.), 29th Annual Conference on Neural Information Processing Systems 2015: Montreal, Canada, 7-12 December 2015 (Vol. 4, pp. 3438-3446). (Advances in Neural Information Processing Systems; Vol. 28). Curran Associates. http://papers.nips.cc/paper/5965-bayesian-dark-knowledge
  • Open Access
    Cohen, T. S., & Welling, M. (2015). Transformation Properties of Learned Visual Representations. In ICLR 2015: accepted papers - Main Conference - Poster Presentations ArXiv. http://arxiv.org/abs/1412.7659
  • Open Access
    Meeds, E., & Welling, M. (2015). Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference. In C. Cortes, N. D. Lawrence, D. D. Lee, M. Sugiyama, & R. Garnett (Eds.), 29th Annual Conference on Neural Information Processing Systems 2015: Montreal, Canada, 7-12 December 2015 (Vol. 3, pp. 2080-2088). (Advances in Neural Information Processing Systems; Vol. 28). Curran Associates. http://papers.nips.cc/paper/5881-optimization-monte-carlo-efficient-and-embarrassingly-parallel-likelihood-free-inference
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