Tom Heskes
20 papers · 2003–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Renaissance Researcher (7) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (14) π£ Hot Topic Early Bird
π
Renaissance Researcher
(7)
πΊοΈ
Taxonomy Completionist
(14)
π§
Keyword Pioneer
π
Keyword Trendsetter Combo
(3)
π
Keyword Champion
ποΈ
Keyword Collector
(88)
π
Conference Pioneer
π
Trend Setter
π
Century Club
(20)
β
The Questioner
Conferences
JMLR (5)
NIPS (5)
PGM (3)
AISTATS (2)
UAI (2)
ACL (1)
CLEAR (1)
IJCAI (1)
Top co-authors
Keywords
bayesian inference
(5)
causal discovery
(5)
expectation propagation
(4)
causal inference
(3)
instrumental variable
(2)
laplace approximation
(2)
posterior marginal
(2)
latent gaussian model
(2)
constraint-based method
(2)
transfer learning
(1)
causal effect estimation
(1)
expectation maximization
(1)
model interpretability
(1)
bioinformatics
(1)
variational inference
(1)
unsupervised learning
(1)
map estimation
(1)
source localization
(1)
approximate inference
(1)
nearest neighbor
(1)
Papers
Bias-variance decompositions: the exclusive privilege of Bregman divergences
JMLR 2025
Offline Changepoint Detection With Gaussian Processes
UAI 2025
AutoCD: Automated Machine Learning for Causal Discovery Algorithms
PGM 2024
Unsupervised Anomaly Detection Algorithms on Real-world Data: How Many Do We Need?
JMLR 2024
Beyond the Markov Equivalence Class: Extending Causal Discovery under Latent Confounding
CLEAR 2023
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models
NIPS 2020
MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models
UAI 2020
A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks
PGM 2018
Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness
AISTATS 2017
Computing Lower and Upper Bounds on the Probability of Causal Statements
PGM 2016
Unsupervised Feature Learning for Visual Sign Language Identification
ACL 2014
Bayesian Probabilities for Constraint-Based Causal Discovery
IJCAI 2013
Approximate Marginals in Latent Gaussian Models
JMLR 2011
On Causal Discovery with Cyclic Additive Noise Models
NIPS 2011
Improving posterior marginal approximations in latent Gaussian models
AISTATS 2010
Causal discovery in multiple models from different experiments
NIPS 2010
Bayesian Source Localization with the Multivariate Laplace Prior
NIPS 2009
Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach
NIPS 2007
Change Point Problems in Linear Dynamical Systems
JMLR 2005
Task Clustering and Gating for Bayesian Multitask Learning
JMLR 2003