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Results: 7
Number of items: 7
  • 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
  • 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
  • Open Access
    Chiang, M., Cinquin, A., Paz, A., Meeds, E., Price, C. A., Welling, M., & Cinquin, O. (2015). Control of Caenorhabditis elegans germ-line stem-cell cycling speed meets requirements of design to minimize mutation accumulation. BMC Biology, 13, Article 51. https://doi.org/10.1186/s12915-015-0148-y
  • Open Access
    Meeds, E., Chiang, M., Lee, M., Cinquin, O., Lowengrub, J., & Welling, M. (2015). POPE: Post Optimization Posterior Evaluation of Likelihood Free Models. BMC Bioinformatics, 16, Article 264. https://doi.org/10.1186/s12859-015-0658-1
  • Open Access
    Meeds, E., Hendriks, R., Al Faraby, S., Bruntink, M., & Welling, M. (2015). MLitB: Machine Learning in the Browser. PeerJ Computer Science, 1, Article e11. https://doi.org/10.7717/peerj-cs.11
  • Meeds, E., & Welling, M. (2014). GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation. In N. Zhang, & J. Tian (Eds.), Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence: Quebec City, Quebec, Canada: July 23-27, 2014: UAI2014 (pp. 593-602). AUAI Press. http://auai.org//uai2014/proceedings/uai-2014-proceedings.pdf
  • Open Access
    Meeds, E., Hendriks, R., al Faraby, S., Bruntink, M., & Welling, M. (2014). MLitB: Machine Learning in the Browser. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.1412.2432
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