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Results: 157
Number of items: 157
  • 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
    Ahn, S., Korattikara, A., Liu, N., Rajan, S., & Welling, M. (2015). Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC. In KDD'15: proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining: August 10-13, 2015, Sydney, Australia (pp. 9-18). Association for Computing Machinery. https://doi.org/10.1145/2783258.2783373
  • 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
  • Chen, Y., Gelfand, A. E., & Welling, M. (2014). Herding for Structured Prediction. In S. Nowozin, P. V. Gehler, J. Jancsary, & C. H. Lampert (Eds.), Advanced structured prediction (pp. 187-212). (Neural information processing series). The MIT Press. https://mitpress.mit.edu/books/advanced-structured-prediction
  • Burges, C. J. C., Bottou, L., Welling, M., Ghahramani, Z., & Weinberger, K. Q. (2014). 27th Annual Conference on Neural Information Processing Systems 2013: December 5-10, Lake Tahoe, Nevada, USA. (Advances in Neural Information Processing Systems; Vol. 26). Curran. http://papers.nips.cc/book/advances-in-neural-information-processing-systems-26-2013
  • 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
    Welling, M. (2014). Van veel data, snelle computers en complexe modellen tot lerende machines. (Oratiereeks). Universiteit van Amsterdam. http://www.oratiereeks.nl/upload/pdf/PDF-8573weboratie_Welling_HR.pdf
  • Open Access
    DuBois, C., Korattikara, A., Welling, M., & Smyth, P. (2014). Approximate Slice Sampling for Bayesian Posterior Inference. JMLR Workshop and Conference Proceedings, 33, 185-193. http://jmlr.org/proceedings/papers/v33/dubois14.html
  • Open Access
    Kingma, D. P., & Welling, M. (2014). Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets. JMLR Workshop and Conference Proceedings, 32, 1782-1790. http://jmlr.org/proceedings/papers/v32/kingma14.html
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