Carl Henrik Ek

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 61

Top Topics

Gaussian Process

Top Venues

Publications

Hrittik Roy, Marco Miani, Carl Henrik Ek, Philipp Hennig, Marvin Pförtner, Lukas Tatzel, Søren Hauberg
Reparameterization invariance in approximate Bayesian inference. CoRR (2024)
Sonja Schlenz, Simon Mößner, Carl Henrik Ek, Fabian Duddeck
Representing engineering design changes in finite element models using directed point cloud autoencoders. Adv. Eng. Informatics 59 (2024)
Aidan Scannell, Carl Henrik Ek, Arthur Richards
Mode-constrained Model-based Reinforcement Learning via Gaussian Processes. AISTATS (2023)
Sonja Schlenz, Simon Mößner, Carl Henrik Ek, Fabian Duddeck
A Flexible Approach for Retrieving Geometrically Similar Finite Element Models Using Point Cloud Autoencoders. KDIR (2023)
Haoting Zhang, Carl Henrik Ek, Magnus Rattray, Marta Milo
SynBa: improved estimation of drug combination synergies with uncertainty quantification. Bioinform. 39 (Supplement-1) (2023)
Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg
Identifying latent distances with Finslerian geometry. Trans. Mach. Learn. Res. 2023 (2023)
Mala Virdee, Markus Kaiser, Emily Shuckburgh, Carl Henrik Ek, Ieva Kazlauskaite
Optimisation of a global climate model ensemble for prediction of extreme heat days. CoRR (2022)
Olga Mikheeva, Ieva Kazlauskaite, Adam Hartshorne, Hedvig Kjellström, Carl Henrik Ek, Neill D. F. Campbell
Aligned Multi-Task Gaussian Process. AISTATS (2022)
Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg
Identifying latent distances with Finslerian geometry. CoRR (2022)
Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande
Deep Neural Networks as Point Estimates for Deep Gaussian Processes. CoRR (2021)
Aidan Scannell, Carl Henrik Ek, Arthur Richards
Trajectory Optimisation in Learned Multimodal Dynamical Systems via Latent-ODE Collocation. ICRA (2021)
Olga Mikheeva, Ieva Kazlauskaite, Adam Hartshorne, Hedvig Kjellström, Carl Henrik Ek, Neill D. F. Campbell
Aligned Multi-Task Gaussian Process. CoRR (2021)
Andreas C. Damianou, Neil D. Lawrence, Carl Henrik Ek
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis. J. Mach. Learn. Res. 22 (2021)
Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande
Deep Neural Networks as Point Estimates for Deep Gaussian Processes. NeurIPS (2021)
Erik Bodin, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek
Black-box density function estimation using recursive partitioning. ICML (2021)
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek
Modulating Surrogates for Bayesian Optimization. ICML (2020)
Markus Kaiser, Clemens Otte, Thomas A. Runkler, Carl Henrik Ek
Bayesian decomposition of multi-modal dynamical systems for reinforcement learning. Neurocomputing 416 (2020)
Erik Bodin, Zhenwen Dai, Neill D. F. Campbell, Carl Henrik Ek
Black-box density function estimation using recursive partitioning. CoRR (2020)
Olga Mikheeva, Ieva Kazlauskaite, Hedvig Kjellström, Carl Henrik Ek
Bayesian nonparametric shared multi-sequence time series segmentation. CoRR (2020)
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell
Monotonic Gaussian Process Flows. AISTATS (2020)
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek
Compositional uncertainty in deep Gaussian processes. UAI (2020)
Gabriela Zarzar Gandler, Carl Henrik Ek, Mårten Björkman, Rustam Stolkin, Yasemin Bekiroglu
Object shape estimation and modeling, based on sparse Gaussian process implicit surfaces, combining visual data and tactile exploration. Robotics Auton. Syst. 126 (2020)
Markus Kaiser, Clemens Otte, Thomas A. Runkler, Carl Henrik Ek
interpretable dynamics models for data-efficient reinforcement learning. ESANN (2019)
Markus Kaiser, Clemens Otte, Thomas A. Runkler, Carl Henrik Ek
Interpretable Dynamics Models for Data-Efficient Reinforcement Learning. CoRR (2019)
Markus Kaiser, Clemens Otte, Thomas A. Runkler, Carl Henrik Ek
Data Association with Gaussian Processes. ECML/PKDD (2) (2019)
Martin Hjelm, Carl Henrik Ek, Renaud Detry, Danica Kragic
Invariant Feature Mappings for Generalizing Affordance Understanding Using Regularized Metric Learning. CoRR (2019)
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Neill D. F. Campbell, Carl Henrik Ek
Modulated Bayesian Optimization using Latent Gaussian Process Models. CoRR (2019)
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek
Compositional uncertainty in deep Gaussian processes. CoRR (2019)
Andrew R. Lawrence, Carl Henrik Ek, Neill D. F. Campbell
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures. ICML (2019)
Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell
Gaussian Process Latent Variable Alignment Learning. AISTATS (2019)
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell
Monotonic Gaussian Process Flow. CoRR (2019)
Ieva Kazlauskaite, Ivan Ustyuzhaninov, Carl Henrik Ek, Neill D. F. Campbell
Sequence Alignment with Dirichlet Process Mixtures. CoRR (2018)
Olga Mikheeva, Carl Henrik Ek, Hedvig Kjellström
Perceptual Facial Expression Representation. FG (2018)
Andrew R. Lawrence, Carl Henrik Ek, Neill D. F. Campbell
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures. CoRR (2018)
Song Liu, Wittawat Jitkrittum, Carl Henrik Ek
Model Inference with Stein Density Ratio Estimation. CoRR (2018)
Sergio Caccamo, Yasemin Bekiroglu, Carl Henrik Ek, Danica Kragic
Active Exploration Using Gaussian Random Fields and Gaussian Process Implicit Surfaces. CoRR (2018)
Alessandro Di Martino, Erik Bodin, Carl Henrik Ek, Neill D. F. Campbell
Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation. ACCV (4) (2018)
Alessandro Di Martino, Erik Bodin, Carl Henrik Ek, Neill D. F. Campbell
Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation. CoRR (2018)
Markus Kaiser, Clemens Otte, Thomas A. Runkler, Carl Henrik Ek
Multimodal Deep Gaussian Processes. CoRR (2018)
Markus Kaiser, Clemens Otte, Thomas A. Runkler, Carl Henrik Ek
Bayesian Alignments of Warped Multi-Output Gaussian Processes. NeurIPS (2018)
Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell
Gaussian Process Latent Variable Alignment Learning. CoRR (2018)
Erik Bodin, Iman Malik, Carl Henrik Ek, Neill D. F. Campbell
Nonparametric Inference for Auto-Encoding Variational Bayes. CoRR (2017)
Markus Kaiser, Clemens Otte, Thomas A. Runkler, Carl Henrik Ek
Bayesian Alignments of Warped Multi-Output Gaussian Processes. CoRR (2017)
Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek
Latent Gaussian Process Regression. CoRR (2017)
Andreas C. Damianou, Neil D. Lawrence, Carl Henrik Ek
Manifold Alignment Determination: finding correspondences across different data views. CoRR (2017)
Iman Malik, Carl Henrik Ek
Neural Translation of Musical Style. CoRR (2017)
Sergio Caccamo, Yasemin Bekiroglu, Carl Henrik Ek, Danica Kragic
Active exploration using Gaussian Random Fields and Gaussian Process Implicit Surfaces. IROS (2016)
Fariba Yousefi, Zhenwen Dai, Carl Henrik Ek, Neil D. Lawrence
Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model. CoRR (2016)
Andreas C. Damianou, Neil D. Lawrence, Carl Henrik Ek
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis. CoRR (2016)
Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek, Bo C. Bertilson
Diagnostic Prediction Using Discomfort Drawings with IBTM. MLHC (2016)
Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek
Inter-battery Topic Representation Learning. ECCV (8) (2016)
Yasemin Bekiroglu, Andreas C. Damianou, Renaud Detry, Johannes A. Stork, Danica Kragic, Carl Henrik Ek
Probabilistic consolidation of grasp experience. ICRA (2016)
Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek, Bo C. Bertilson
Diagnostic Prediction Using Discomfort Drawings with IBTM. CoRR (2016)
Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek
Inter-Battery Topic Representation Learning. CoRR (2016)
Martin Hjelm, Carl Henrik Ek, Renaud Detry, Danica Kragic
Learning Human Priors for Task-Constrained Grasping. ICVS (2015)
Johannes A. Stork, Carl Henrik Ek, Danica Kragic
Learning Predictive State Representations for planning. IROS (2015)
Andrea Baisero, Florian T. Pokorny, Carl Henrik Ek
On a Family of Decomposable Kernels on Sequences. CoRR (2015)
Andreas C. Damianou, Carl Henrik Ek, Luke Boorman, Neil D. Lawrence, Tony J. Prescott
A Top-Down Approach for a Synthetic Autobiographical Memory System. Living Machines (2015)
Dan Song, Carl Henrik Ek, Kai Huebner, Danica Kragic
Task-Based Robot Grasp Planning Using Probabilistic Inference. IEEE Trans. Robotics 31 (3) (2015)
Ali Sharif Razavian, Hossein Azizpour, Atsuto Maki, Josephine Sullivan, Carl Henrik Ek, Stefan Carlsson
Persistent Evidence of Local Image Properties in Generic ConvNets. SCIA (2015)
Johannes A. Stork, Carl Henrik Ek, Yasemin Bekiroglu, Danica Kragic
Learning Predictive State Representation for in-hand manipulation. ICRA (2015)
Alessandro Pieropan, Carl Henrik Ek, Hedvig Kjellström
Recognizing object affordances in terms of spatio-temporal object-object relationships. Humanoids (2014)
Mitesh Patel, Jaime Valls Miró, Danica Kragic, Carl Henrik Ek, Gamini Dissanayake
Learning object, grasping and manipulation activities using hierarchical HMMs. Auton. Robots 37 (3) (2014)
Martin Hjelm, Renaud Detry, Carl Henrik Ek, Danica Kragic
Representations for cross-task, cross-object grasp transfer. ICRA (2014)
Heydar Maboudi Afkham, Carl Henrik Ek, Stefan Carlsson
A Topological Framework for Training Latent Variable Models. ICPR (2014)
Ali Sharif Razavian, Hossein Azizpour, Atsuto Maki, Josephine Sullivan, Carl Henrik Ek, Stefan Carlsson
Persistent Evidence of Local Image Properties in Generic ConvNets. CoRR (2014)
Heydar Maboudi Afkham, Carl Henrik Ek, Stefan Carlsson
Gradual Improvement of Image Descriptor Quality. ICPRAM (2014)
Heydar Maboudi Afkham, Carl Henrik Ek, Stefan Carlsson
Initialization Framework for Latent Variable Models. ICPRAM (2014)
Javier Romero, Hedvig Kjellström, Carl Henrik Ek, Danica Kragic
Non-parametric hand pose estimation with object context. Image Vis. Comput. 31 (8) (2013)
Javier Romero, Thomas Feix, Carl Henrik Ek, Hedvig Kjellström, Danica Kragic
Extracting Postural Synergies for Robotic Grasping. IEEE Trans. Robotics 29 (6) (2013)
Andrea Baisero, Florian T. Pokorny, Danica Kragic, Carl Henrik Ek
The Path Kernel. ICPRAM (2013)
Heydar Maboudi Afkham, Carl Henrik Ek, Stefan Carlsson
Qualitative Vocabulary based Descriptor. ICPRAM (2013)
Renaud Detry, Carl Henrik Ek, Marianna Madry, Danica Kragic
Learning a dictionary of prototypical grasp-predicting parts from grasping experience. ICRA (2013)
Cheng Zhang, Carl Henrik Ek, Xavi Gratal, Florian T. Pokorny, Hedvig Kjellström
Supervised Hierarchical Dirichlet Processes with Variational Inference. ICCV Workshops (2013)
Thomas Feix, Javier Romero, Carl Henrik Ek, Heinz-Bodo Schmiedmayer, Danica Kragic
A Metric for Comparing the Anthropomorphic Motion Capability of Artificial Hands. IEEE Trans. Robotics 29 (1) (2013)
Akshaya Thippur, Carl Henrik Ek, Hedvig Kjellström
Inferring hand pose: A comparative study of visual shape features. FG (2013)
Alessandro Pieropan, Carl Henrik Ek, Hedvig Kjellström
Functional object descriptors for human activity modeling. ICRA (2013)
Andrea Baisero, Florian T. Pokorny, Danica Kragic, Carl Henrik Ek
The Path Kernel: A Novel Kernel for Sequential Data. ICPRAM (Selected Papers) (2013)
Cheng Zhang, Carl Henrik Ek, Hedvig Kjellström
Factorized Topic Models ICLR (Workshop Poster) (2013)
Martin Hjelm, Carl Henrik Ek, Renaud Detry, Hedvig Kjellström, Danica Kragic
Sparse summarization of robotic grasping data. ICRA (2013)
Marianna Madry, Heydar Maboudi Afkham, Carl Henrik Ek, Stefan Carlsson, Danica Kragic
Extracting essential local object characteristics for 3D object categorization. IROS (2013)
Mitesh Patel, Carl Henrik Ek, Nikolaos Kyriazis, Antonis A. Argyros, Jaime Valls Miró, Danica Kragic
Language for learning complex human-object interactions. ICRA (2013)
Alexander Davies, Carl Henrik Ek, Colin J. Dalton, Neill W. Campbell
Generating 3D Morphable Model Parameters for Facial Tracking - Factorising Identity and Expression. GRAPP/IVAPP (2012)
Andreas C. Damianou, Carl Henrik Ek, Michalis K. Titsias, Neil D. Lawrence
Manifold Relevance Determination CoRR (2012)
Marianna Madry, Carl Henrik Ek, Renaud Detry, Kaiyu Hang, Danica Kragic
Improving generalization for 3D object categorization with Global Structure Histograms. IROS (2012)
Niklas Bergström, Carl Henrik Ek, Danica Kragic, Yuji Yamakawa, Taku Senoo, Masatoshi Ishikawa
On-line learning of temporal state models for flexible objects. Humanoids (2012)
Florian T. Pokorny, Carl Henrik Ek, Hedvig Kjellström, Danica Kragic
Persistent Homology for Learning Densities with Bounded Support. NIPS (2012)
Renaud Detry, Carl Henrik Ek, Marianna Madry, Justus H. Piater, Danica Kragic
Generalizing grasps across partly similar objects. ICRA (2012)
Andreas C. Damianou, Carl Henrik Ek, Michalis K. Titsias, Neil D. Lawrence
Manifold Relevance Determination. ICML (2012)
Guoliang Luo, Niklas Bergström, Carl Henrik Ek, Danica Kragic
Representing actions with Kernels. IROS (2011)
Dan Song, Carl Henrik Ek, Kai Huebner, Danica Kragic
Multivariate discretization for Bayesian Network structure learning in robot grasping. ICRA (2011)
Dan Song, Carl Henrik Ek, Kai Huebner, Danica Kragic
Embodiment-specific representation of robot grasping using graphical models and latent-space discretization. IROS (2011)
Alexander Davies, Carl Henrik Ek, Colin J. Dalton, Neill W. Campbell
Facial Movement Based Recognition. MIRAGE (2011)
Carl Henrik Ek, Danica Kragic
The Importance of Structure. ISRR (2011)
Niklas Bergström, Carl Henrik Ek, Mårten Björkman, Danica Kragic
Scene Understanding through Autonomous Interactive Perception. ICVS (2011)
Carl Henrik Ek, Dan Song, Kai Huebner, Danica Kragic
Task modeling in imitation learning using latent variable models. Humanoids (2010)
Mathieu Salzmann, Carl Henrik Ek, Raquel Urtasun, Trevor Darrell
Factorized Orthogonal Latent Spaces. AISTATS (2010)
Carl Henrik Ek, Jonathan Rihan, Philip H. S. Torr, Grégory Rogez, Neil D. Lawrence
Ambiguity Modeling in Latent Spaces. MLMI (2008)
Carl Henrik Ek, Philip H. S. Torr, Neil D. Lawrence
Gaussian Process Latent Variable Models for Human Pose Estimation. MLMI (2007)