dhr. dr. E.W.F. (Ted) Meeds

  • Faculteit der Natuurwetenschappen, Wiskunde en Informatica
  • Bezoekadres
    Science Park A
    Science Park 904  Amsterdam
  • Postadres:
    Postbus  94214
    1090 GE  Amsterdam
  • E.W.F.Meeds@uva.nl


  • 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, [264]. DOI: 10.1186/s12859-015-0658-1 [details] [PDF]
  • Meeds, E., Hendriks, R., Faraby, S., Bruntink, M., & Welling, M. (2015). MLitB: Machine Learning in the Browser. PeerJ Computer Science[details]
  • 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). Corvallis, OR: AUAI Press. [details]
  • Meeds, E., & Welling, M. (2015). Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference. Advances in Neural Information Processing Systems, 28, 2080-2088. [details] [PDF]
  • 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, [51]. DOI: 10.1186/s12915-015-0148-y [details] [PDF]


  • 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). Corvallis, Oregon: AUAI Press. [details]


  • Meeds, E., & Welling, M. (2013). Inference in Stochastic Biological Systems using Gaussian Process Surrogate ABC. In Proceedings of Biocomp Workshop at Neural Information Processing Systems (NIPS, 2013). [details]
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