Hannes Nickisch
13 papers · 2008–2019 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (26) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
π
Keyword Champion
π§
Keyword Pioneer
π
Keyword Trendsetter Combo
(3)
π
Trend Setter
π₯
Unstoppable Β· Bronze
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Conference Pioneer
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Renaissance Researcher
(5)
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Century Club Β· Bronze
ποΈ
Keyword Collector
(59)
Top co-authors
Research topics
Machine Learning
(13)
Artificial Intelligence
(9)
Bayesian & Probabilistic Β· Artificial Intelligence
(8)
Optimization & Theory
(8)
Core Methods
(7)
Bayesian & Probabilistic Β· Machine Learning
(5)
Mathematics & Optimization
(4)
Optimization
(4)
Data Science & Analytics
(2)
Deep Learning
(2)
Application Areas
(2)
Architectures
(2)
Methods
(2)
Computer Vision
(1)
Healthcare & Medicine
(1)
Keywords
gaussian process
(9)
expectation propagation
(5)
variational inference
(5)
kernel learning
(4)
bayesian inference
(3)
laplace approximation
(2)
approximate inference
(2)
change point detection
(2)
gaussian processes
(2)
binary classification
(1)
image segmentation
(1)
regression
(1)
spatio-temporal modeling
(1)
natural image statistics
(1)
medical imaging
(1)
sequence optimization
(1)
magnetic resonance imaging
(1)
bayesian experimental design
(1)
model selection
(1)
time series analysis
(1)
Papers
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction
JMLR 2019
Dynamic Pacemaker Artifact Removal (DyPAR) from CT Data using CNNs
MIDL 2019
State Space Gaussian Processes with Non-Gaussian Likelihood
ICML 2018
Scalable Log Determinants for Gaussian Process Kernel Learning
NeurIPS 2017
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces
AISTATS 2016
Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods
ICML 2015
Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)
ICML 2015
glm-ie: Generalised Linear Models Inference & Estimation Toolbox
JMLR 2012
Additive Gaussian Processes
NeurIPS 2011
Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference
AISTATS 2011
Gaussian Processes for Machine Learning (GPML) Toolbox
JMLR 2010
Approximations for Binary Gaussian Process Classification
JMLR 2008
Bayesian Experimental Design of Magnetic Resonance Imaging Sequences
NeurIPS 2008