Gaussian Process Latent Variable Models for Human Pose Estimation. - Carl Henrik Ek; Philip H. S. Torr; Neil D. Lawrence (MLMI, 2007)

Ambiguity Modeling in Latent Spaces. - Carl Henrik Ek; Jonathan Rihan; Philip H. S. Torr; Grégory Rogez; Neil D. Lawrence (MLMI, 2008)

Task modeling in imitation learning using latent variable models. - Carl Henrik Ek; Dan Song 002; Kai Huebner; Danica Kragic (Humanoids, 2010)

Factorized Orthogonal Latent Spaces. - Mathieu Salzmann; Carl Henrik Ek; Raquel Urtasun; Trevor Darrell (AISTATS, 2010)

Multivariate discretization for Bayesian Network structure learning in robot grasping. - Dan Song 002; Carl Henrik Ek; Kai Huebner; Danica Kragic (ICRA, 2011)

Scene Understanding through Autonomous Interactive Perception. - Niklas Bergström; Carl Henrik Ek; Mårten Björkman; Danica Kragic (ICVS, 2011)

Representing actions with Kernels. - Guoliang Luo; Niklas Bergström; Carl Henrik Ek; Danica Kragic (IROS, 2011)

Embodiment-specific representation of robot grasping using graphical models and latent-space discretization. - Dan Song 002; Carl Henrik Ek; Kai Huebner; Danica Kragic (IROS, 2011)

The Importance of Structure. - Carl Henrik Ek; Danica Kragic (ISRR, 2011)

Facial Movement Based Recognition. - Alexander Davies; Carl Henrik Ek; Colin J. Dalton; Neill W. Campbell (MIRAGE, 2011)

Generating 3D Morphable Model Parameters for Facial Tracking - Factorising Identity and Expression. - Alexander Davies; Carl Henrik Ek; Colin J. Dalton; Neill W. Campbell (GRAPP/IVAPP, 2012)

On-line learning of temporal state models for flexible objects. - Niklas Bergström; Carl Henrik Ek; Danica Kragic; Yuji Yamakawa; Taku Senoo; Masatoshi Ishikawa (Humanoids, 2012)

Manifold Relevance Determination. - Andreas C. Damianou; Carl Henrik Ek; Michalis K. Titsias; Neil D. Lawrence (ICML, 2012)

Generalizing grasps across partly similar objects. - Renaud Detry; Carl Henrik Ek; Marianna Madry; Justus H. Piater; Danica Kragic (ICRA, 2012)

Improving generalization for 3D object categorization with Global Structure Histograms. - Marianna Madry; Carl Henrik Ek; Renaud Detry; Kaiyu Hang; Danica Kragic (IROS, 2012)

Persistent Homology for Learning Densities with Bounded Support. - Florian T. Pokorny; Carl Henrik Ek; Hedvig Kjellström; Danica Kragic (NIPS, 2012)

Inferring hand pose: A comparative study of visual shape features. - Akshaya Thippur; Carl Henrik Ek; Hedvig Kjellström (FG, 2013)

Supervised Hierarchical Dirichlet Processes with Variational Inference. - Cheng Zhang 005; Carl Henrik Ek; Xavi Gratal; Florian T. Pokorny; Hedvig Kjellström (ICCV Workshops, 2013)

Qualitative Vocabulary based Descriptor. - Heydar Maboudi Afkham; Carl Henrik Ek; Stefan Carlsson (ICPRAM, 2013)

The Path Kernel. - Andrea Baisero; Florian T. Pokorny; Danica Kragic; Carl Henrik Ek (ICPRAM, 2013)

The Path Kernel: A Novel Kernel for Sequential Data. - Andrea Baisero; Florian T. Pokorny; Danica Kragic; Carl Henrik Ek (ICPRAM (Selected Papers), 2013)

Learning a dictionary of prototypical grasp-predicting parts from grasping experience. - Renaud Detry; Carl Henrik Ek; Marianna Madry; Danica Kragic (ICRA, 2013)

Sparse summarization of robotic grasping data. - Martin Hjelm; Carl Henrik Ek; Renaud Detry; Hedvig Kjellström; Danica Kragic (ICRA, 2013)

Language for learning complex human-object interactions. - Mitesh Patel; Carl Henrik Ek; Nikolaos Kyriazis; Antonis A. Argyros; Jaime Valls Miró; Danica Kragic (ICRA, 2013)

Functional object descriptors for human activity modeling. - Alessandro Pieropan; Carl Henrik Ek; Hedvig Kjellström (ICRA, 2013)

Extracting essential local object characteristics for 3D object categorization. - Marianna Madry; Heydar Maboudi Afkham; Carl Henrik Ek; Stefan Carlsson; Danica Kragic (IROS, 2013)

Factorized Topic Models - Cheng Zhang 005; Carl Henrik Ek; Hedvig Kjellström (ICLR (Workshop Poster), 2013)

Non-parametric hand pose estimation with object context. - Javier Romero 002; Hedvig Kjellström; Carl Henrik Ek; Danica Kragic (Image Vis. Comput., 2013)

A Metric for Comparing the Anthropomorphic Motion Capability of Artificial Hands. - Thomas Feix; Javier Romero 002; Carl Henrik Ek; Heinz-Bodo Schmiedmayer; Danica Kragic (IEEE Trans. Robotics, 2013)

Extracting Postural Synergies for Robotic Grasping. - Javier Romero 002; Thomas Feix; Carl Henrik Ek; Hedvig Kjellström; Danica Kragic (IEEE Trans. Robotics, 2013)

Recognizing object affordances in terms of spatio-temporal object-object relationships. - Alessandro Pieropan; Carl Henrik Ek; Hedvig Kjellström (Humanoids, 2014)

A Topological Framework for Training Latent Variable Models. - Heydar Maboudi Afkham; Carl Henrik Ek; Stefan Carlsson (ICPR, 2014)

Initialization Framework for Latent Variable Models. - Heydar Maboudi Afkham; Carl Henrik Ek; Stefan Carlsson (ICPRAM, 2014)

Gradual Improvement of Image Descriptor Quality. - Heydar Maboudi Afkham; Carl Henrik Ek; Stefan Carlsson (ICPRAM, 2014)

Representations for cross-task, cross-object grasp transfer. - Martin Hjelm; Renaud Detry; Carl Henrik Ek; Danica Kragic (ICRA, 2014)

Learning object, grasping and manipulation activities using hierarchical HMMs. - Mitesh Patel; Jaime Valls Miró; Danica Kragic; Carl Henrik Ek; Gamini Dissanayake (Auton. Robots, 2014)

Learning Predictive State Representation for in-hand manipulation. - Johannes A. Stork; Carl Henrik Ek; Yasemin Bekiroglu; Danica Kragic (ICRA, 2015)

Learning Human Priors for Task-Constrained Grasping. - Martin Hjelm; Carl Henrik Ek; Renaud Detry; Danica Kragic (ICVS, 2015)

Learning Predictive State Representations for planning. - Johannes A. Stork; Carl Henrik Ek; Danica Kragic (IROS, 2015)

A Top-Down Approach for a Synthetic Autobiographical Memory System. - Andreas C. Damianou; Carl Henrik Ek; Luke Boorman; Neil D. Lawrence; Tony J. Prescott (Living Machines, 2015)

Persistent Evidence of Local Image Properties in Generic ConvNets. - Ali Sharif Razavian; Hossein Azizpour; Atsuto Maki; Josephine Sullivan; Carl Henrik Ek; Stefan Carlsson (SCIA, 2015)

On a Family of Decomposable Kernels on Sequences. - Andrea Baisero; Florian T. Pokorny; Carl Henrik Ek (CoRR, 2015)

Task-Based Robot Grasp Planning Using Probabilistic Inference. - Dan Song 002; Carl Henrik Ek; Kai Huebner; Danica Kragic (IEEE Trans. Robotics, 2015)

Inter-battery Topic Representation Learning. - Cheng Zhang 005; Hedvig Kjellström; Carl Henrik Ek (ECCV (8), 2016)

Probabilistic consolidation of grasp experience. - Yasemin Bekiroglu; Andreas C. Damianou; Renaud Detry; Johannes A. Stork; Danica Kragic; Carl Henrik Ek (ICRA, 2016)

Active exploration using Gaussian Random Fields and Gaussian Process Implicit Surfaces. - Sergio Caccamo; Yasemin Bekiroglu; Carl Henrik Ek; Danica Kragic (IROS, 2016)

Diagnostic Prediction Using Discomfort Drawings with IBTM. - Cheng Zhang 005; Hedvig Kjellström; Carl Henrik Ek; Bo C. Bertilson (MLHC, 2016)

Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model. - Fariba Yousefi; Zhenwen Dai; Carl Henrik Ek; Neil D. Lawrence (CoRR, 2016)

Latent Gaussian Process Regression. - Erik Bodin; Neill D. F. Campbell; Carl Henrik Ek (CoRR, 2017)

Manifold Alignment Determination: finding correspondences across different data views. - Andreas C. Damianou; Neil D. Lawrence; Carl Henrik Ek (CoRR, 2017)

Neural Translation of Musical Style. - Iman Malik; Carl Henrik Ek (CoRR, 2017)

Nonparametric Inference for Auto-Encoding Variational Bayes. - Erik Bodin; Iman Malik; Carl Henrik Ek; Neill D. F. Campbell (CoRR, 2017)

Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation. - Alessandro Di Martino; Erik Bodin; Carl Henrik Ek; Neill D. F. Campbell (ACCV (4), 2018)

Perceptual Facial Expression Representation. - Olga Mikheeva; Carl Henrik Ek; Hedvig Kjellström (FG, 2018)

Bayesian Alignments of Warped Multi-Output Gaussian Processes. - Markus Kaiser 001; Clemens Otte; Thomas A. Runkler; Carl Henrik Ek (NeurIPS, 2018)

Model Inference with Stein Density Ratio Estimation. - Song Liu 002; Wittawat Jitkrittum; Carl Henrik Ek (CoRR, 2018)

Multimodal Deep Gaussian Processes. - Markus Kaiser 001; Clemens Otte; Thomas A. Runkler; Carl Henrik Ek (CoRR, 2018)

Sequence Alignment with Dirichlet Process Mixtures. - Ieva Kazlauskaite; Ivan Ustyuzhaninov; Carl Henrik Ek; Neill D. F. Campbell (CoRR, 2018)

Gaussian Process Latent Variable Alignment Learning. - Ieva Kazlauskaite; Carl Henrik Ek; Neill D. F. Campbell (AISTATS, 2019)

interpretable dynamics models for data-efficient reinforcement learning. - Markus Kaiser 001; Clemens Otte; Thomas A. Runkler; Carl Henrik Ek (ESANN, 2019)

DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures. - Andrew R. Lawrence; Carl Henrik Ek; Neill D. F. Campbell (ICML, 2019)

Data Association with Gaussian Processes. - Markus Kaiser 001; Clemens Otte; Thomas A. Runkler; Carl Henrik Ek (ECML/PKDD (2), 2019)

Invariant Feature Mappings for Generalizing Affordance Understanding Using Regularized Metric Learning. - Martin Hjelm; Carl Henrik Ek; Renaud Detry; Danica Kragic (CoRR, 2019)

Monotonic Gaussian Process Flow. - Ivan Ustyuzhaninov; Ieva Kazlauskaite; Carl Henrik Ek; Neill D. F. Campbell (CoRR, 2019)

Modulated Bayesian Optimization using Latent Gaussian Process Models. - Erik Bodin; Markus Kaiser 001; Ieva Kazlauskaite; Neill D. F. Campbell; Carl Henrik Ek (CoRR, 2019)

Monotonic Gaussian Process Flows. - Ivan Ustyuzhaninov; Ieva Kazlauskaite; Carl Henrik Ek; Neill D. F. Campbell (AISTATS, 2020)

Modulating Surrogates for Bayesian Optimization. - Erik Bodin; Markus Kaiser 001; Ieva Kazlauskaite; Zhenwen Dai; Neill W. Campbell; Carl Henrik Ek (ICML, 2020)

Compositional uncertainty in deep Gaussian processes. - Ivan Ustyuzhaninov; Ieva Kazlauskaite; Markus Kaiser 001; Erik Bodin; Neill D. F. Campbell; Carl Henrik Ek (UAI, 2020)

Bayesian nonparametric shared multi-sequence time series segmentation. - Olga Mikheeva; Ieva Kazlauskaite; Hedvig Kjellström; Carl Henrik Ek (CoRR, 2020)

Black-box density function estimation using recursive partitioning. - Erik Bodin; Zhenwen Dai; Neill D. F. Campbell; Carl Henrik Ek (CoRR, 2020)

Bayesian decomposition of multi-modal dynamical systems for reinforcement learning. - Markus Kaiser 001; Clemens Otte; Thomas A. Runkler; Carl Henrik Ek (Neurocomputing, 2020)

Object shape estimation and modeling, based on sparse Gaussian process implicit surfaces, combining visual data and tactile exploration. - Gabriela Zarzar Gandler; Carl Henrik Ek; Mårten Björkman; Rustam Stolkin; Yasemin Bekiroglu (Robotics Auton. Syst., 2020)

Black-box density function estimation using recursive partitioning. - Erik Bodin; Zhenwen Dai; Neill W. Campbell; Carl Henrik Ek (ICML, 2021)

Trajectory Optimisation in Learned Multimodal Dynamical Systems via Latent-ODE Collocation. - Aidan Scannell; Carl Henrik Ek; Arthur Richards (ICRA, 2021)

Deep Neural Networks as Point Estimates for Deep Gaussian Processes. - Vincent Dutordoir; James Hensman; Mark van der Wilk; Carl Henrik Ek; Zoubin Ghahramani; Nicolas Durrande (NeurIPS, 2021)

Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis. - Andreas C. Damianou; Neil D. Lawrence; Carl Henrik Ek (J. Mach. Learn. Res., 2021)

Aligned Multi-Task Gaussian Process. - Olga Mikheeva; Ieva Kazlauskaite; Adam Hartshorne; Hedvig Kjellström; Carl Henrik Ek; Neill D. F. Campbell (AISTATS, 2022)

Optimisation of a global climate model ensemble for prediction of extreme heat days. - Mala Virdee; Markus Kaiser 001; Emily Shuckburgh; Carl Henrik Ek; Ieva Kazlauskaite (CoRR, 2022)

Mode-constrained Model-based Reinforcement Learning via Gaussian Processes. - Aidan Scannell; Carl Henrik Ek; Arthur Richards (AISTATS, 2023)

A Flexible Approach for Retrieving Geometrically Similar Finite Element Models Using Point Cloud Autoencoders. - Sonja Schlenz; Simon Mößner; Carl Henrik Ek; Fabian Duddeck (KDIR, 2023)

SynBa: improved estimation of drug combination synergies with uncertainty quantification. - Haoting Zhang; Carl Henrik Ek; Magnus Rattray; Marta Milo (Bioinform., 2023)

Identifying latent distances with Finslerian geometry. - Alison Pouplin; David Eklund; Carl Henrik Ek; Søren Hauberg (Trans. Mach. Learn. Res., 2023)

Reparameterization invariance in approximate Bayesian inference. - Hrittik Roy; Marco Miani; Carl Henrik Ek; Philipp Hennig; Marvin Pförtner; Lukas Tatzel; Søren Hauberg (NeurIPS, 2024)

Representing engineering design changes in finite element models using directed point cloud autoencoders. - Sonja Schlenz; Simon Mößner; Carl Henrik Ek; Fabian Duddeck (Adv. Eng. Informatics, 2024)

Linear combinations of latents in diffusion models: interpolation and beyond. - Erik Bodin; Henry Moss; Carl Henrik Ek (CoRR, 2024)

Variance reduction of diffusion model's gradients with Taylor approximation-based control variate. - Paul Jeha; Will Grathwohl; Michael Riis Andersen; Carl Henrik Ek; Jes Frellsen (CoRR, 2024)

Calabi-Yau metrics through Grassmannian learning and Donaldson's algorithm. - Carl Henrik Ek; Oisin Kim; Challenger Mishra (CoRR, 2024)

Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling. - Jasmine Bayrooti; Carl Henrik Ek; Amanda Prorok (ICLR, 2025)

Linear combinations of latents in generative models: subspaces and beyond. - Erik Bodin; Alexandru I. Stere; Dragos D. Margineantu; Carl Henrik Ek; Henry Moss (ICLR, 2025)

Learning from Preferences and Mixed Demonstrations in General Settings. - Jason Ross Brown; Carl Henrik Ek; Robert D. Mullins (CoRR, 2025)