Barbara Rakitsch
9 papers · 2013–2023 · 5 venues · across top CS/AI venues
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Achievements
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Conference Polyglot · Silver
🏃
Academic Marathon · Half
🌉
Interdisciplinary Bridge · Silver
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Taxonomy Completionist
(21)
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Trend Setter
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Research topics
Machine Learning
(9)
Optimization & Theory · Machine Learning
(6)
Bayesian & Probabilistic · Machine Learning
(5)
Core Methods
(5)
Artificial Intelligence
(4)
Bayesian & Probabilistic · Artificial Intelligence
(4)
Learning Types
(3)
Deep Learning
(2)
Mathematics & Optimization
(2)
Optimization
(2)
Data Science & Analytics
(1)
Architectures
(1)
Learning Paradigms
(1)
Methods
(1)
Optimization & Theory · Deep Learning
(1)
Keywords
gaussian process
(5)
bayesian inference
(3)
variational inference
(3)
time series
(3)
uncertainty quantification
(2)
state space model
(2)
dynamical system
(2)
stochastic differential equation
(2)
epistemic uncertainty
(1)
probabilistic modeling
(1)
laplace approximation
(1)
multi-task gaussian process
(1)
message passing
(1)
parameter inference
(1)
marginal likelihood
(1)
kronecker product
(1)
bayesian regression
(1)
signal processing
(1)
multi-output regression
(1)
sparse approximation
(1)
Papers
Combining Slow and Fast: Complementary Filtering for Dynamics Learning
AAAI 2023
Laplace approximated Gaussian process state-space models
UAI 2022
Learning interacting dynamical systems with latent Gaussian process ODEs
NeurIPS 2022
Safe Active Learning for Multi-Output Gaussian Processes
AISTATS 2022
Traversing Time with Multi-Resolution Gaussian Process State-Space Models
L4DC 2022
Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes
AISTATS 2021
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties
NeurIPS 2020
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds
NeurIPS 2018
It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals
NeurIPS 2013