ei
Rojas-Carulla, M.
Learning Transferable Representations
University of Cambridge, UK, 2019 (phdthesis)
ei
Gu, S.
Sample-efficient deep reinforcement learning for continuous control
University of Cambridge, UK, 2019 (phdthesis)
ei
Ścibior*, A.
Formally justified and modular Bayesian inference for probabilistic programs
University of Cambridge, UK, 2019 (phdthesis)
ei
Xu, J.
Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing
Technical University of Munich, Germany, 2019 (mastersthesis)
ei
Weichwald, S.
Pragmatism and Variable Transformations in Causal Modelling
ETH Zurich, 2019 (phdthesis)
ei
Katiyar, P.
Quantification of tumor heterogeneity using PET/MRI and machine learning
Eberhard Karls Universität Tübingen, Germany, 2019 (phdthesis)
ei
Bauer, M.
Advances in Probabilistic Modelling: Sparse Gaussian Processes, Autoencoders, and Few-shot Learning
University of Cambridge, UK, 2019 (phdthesis)
ei
Gehler, PV.
Kernel Learning Approaches for Image Classification
Biologische Kybernetik, Universität des Saarlandes, Saarbrücken, Germany, October 2009 (phdthesis)
ei
Blaschko, MB.
Kernel Methods in Computer Vision:Object Localization, Clustering,and Taxonomy Discovery
Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, March 2009 (phdthesis)
ei
Mülling, K.
Motor Control and Learning in Table Tennis
Eberhard Karls Universität Tübingen, Gerrmany, 2009 (diplomathesis)
ei
Drewe, P.
Hierarchical Clustering and Density Estimation Based on k-nearest-neighbor graphs
Eberhard Karls Universität Tübingen, Germany, 2009 (diplomathesis)
ei
Nowozin, S.
Learning with Structured Data: Applications to Computer Vision
Technische Universität Berlin, Germany, 2009 (phdthesis)
ei
Steinke, F.
From Differential Equations to Differential Geometry: Aspects of Regularisation in Machine Learning
Universität des Saarlandes, Saarbrücken, Germany, 2009 (phdthesis)