Carl Henrik Ek
16 papers · 2010–2025 · 7 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (25) 🏃 Academic Marathon · Full 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
🗃️
Keyword Collector
(68)
🌈
Renaissance Researcher
(5)
🔥
Unstoppable · Bronze
🚀
Conference Pioneer
💎
Century Club · Bronze
📈
Trend Setter
Top co-authors
Research topics
Machine Learning
(11)
Artificial Intelligence
(9)
Bayesian & Probabilistic · Artificial Intelligence
(9)
Optimization & Theory
(8)
Core Methods
(5)
Deep Learning
(4)
Bayesian & Probabilistic · Machine Learning
(4)
Models
(4)
Data Science & Analytics
(3)
Learning Types
(3)
Methods · Data Science & Analytics
(3)
Computer Vision
(2)
Reinforcement Learning
(2)
Applications
(2)
Methods · Reinforcement Learning
(2)
Keywords
gaussian process
(8)
variational inference
(6)
bayesian inference
(3)
latent variable model
(3)
bayesian nonparametrics
(2)
uncertainty quantification
(2)
latent space
(2)
multi-view learning
(2)
deep gaussian process
(2)
model-based reinforcement learning
(2)
image generation
(1)
gaussian processes
(1)
sequential decision making
(1)
medical imaging
(1)
sample efficiency
(1)
pose estimation
(1)
dirichlet process
(1)
model uncertainty
(1)
posterior distribution
(1)
posterior sampling
(1)
Papers
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
ICLR 2025
Linear combinations of latents in generative models: subspaces and beyond
ICLR 2025
Reparameterization invariance in approximate Bayesian inference
NeurIPS 2024
Mode-constrained Model-based Reinforcement Learning via Gaussian Processes
AISTATS 2023
Aligned Multi-Task Gaussian Process
AISTATS 2022
Black-box density function estimation using recursive partitioning
ICML 2021
Deep Neural Networks as Point Estimates for Deep Gaussian Processes
NeurIPS 2021
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis
JMLR 2021
Compositional uncertainty in deep Gaussian processes
UAI 2020
Modulating Surrogates for Bayesian Optimization
ICML 2020
Monotonic Gaussian Process Flows
AISTATS 2020
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures
ICML 2019
Gaussian Process Latent Variable Alignment Learning
AISTATS 2019
Bayesian Alignments of Warped Multi-Output Gaussian Processes
NeurIPS 2018
Diagnostic Prediction Using Discomfort Drawings with IBTM
MLHC 2016
Factorized Orthogonal Latent Spaces
AISTATS 2010