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Deterministic and Statistical Methods in Machine Learning, First International Workshop, Sheffield, UK, September 7-10, 2004, Revised Lectures

, , and (Eds.) volume 3635 of Lecture Notes in Computer Science, Springer, (2005)

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Extensions of the Informative Vector Machine., , and . Deterministic and Statistical Methods in Machine Learning, volume 3635 of Lecture Notes in Computer Science, page 56-87. Springer, (2004)Solving Schrödinger Bridges via Maximum Likelihood, , , and . (2021)cite arxiv:2106.02081Comment: 9 pages + appendix (total 28 pages).Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling (Dagstuhl Seminar 22382)., , , , and . Dagstuhl Reports, 12 (9): 150-199 (September 2022)Challenges in Deploying Machine Learning: a Survey of Case Studies., , and . CoRR, (2020)Propagating uncertainty in microarray data analysis., , , , and . Briefings Bioinform., 7 (1): 37-47 (2006)TFInfer: a tool for probabilistic inference of transcription factor activities., , , , , and . Bioinform., 26 (20): 2635-2636 (2010)Deep Gaussian Processes for Multi-fidelity Modeling., , , , and . CoRR, (2019)Fast Forward Selection to Speed Up Sparse Gaussian Process Regression., , and . AISTATS, Society for Artificial Intelligence and Statistics, (2003)An integrated probabilistic framework for robot perception, learning and memory., , , , , and . ROBIO, page 1796-1801. IEEE, (2016)Meta-Surrogate Benchmarking for Hyperparameter Optimization., , , , and . NeurIPS, page 6267-6277. (2019)