Joris M. Mooij
24 papers · 2007–2024 · 3 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (3) π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer π Academic Marathon (17)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Interdisciplinary Bridge
π¬
Deep Specialist
(13)
π
Keyword Champion
(2)
ποΈ
Keyword Collector
(96)
π
Trend Setter
π
Century Club
(24)
π₯
Unstoppable
(9)
π
Conference Pioneer
Conferences
UAI (9)
NIPS (8)
JMLR (7)
Top co-authors
Keywords
causal discovery
(9)
causal inference
(6)
graphical model
(6)
additive noise model
(4)
structural causal model
(4)
probabilistic inference
(3)
belief propagation
(3)
factor graph
(3)
causal ordering
(2)
approximate inference
(2)
causal identifiability
(2)
feedback loop
(2)
conditional independence
(2)
observational datum
(2)
dynamical system
(2)
additive noise
(2)
bayesian network
(2)
structural equation model
(2)
causal effect
(2)
selection bia
(2)
Papers
Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence β Preface
UAI 2024
Establishing Markov equivalence in cyclic directed graphs
UAI 2023
Correcting for selection bias and missing response in regression using privileged information
UAI 2023
Robustness of model predictions under extension
UAI 2022
A Bayesian nonparametric conditional two-sample test with an application to Local Causal Discovery
UAI 2021
Conditional independences and causal relations implied by sets of equations
JMLR 2021
A weaker faithfulness assumption based on triple interactions
UAI 2021
Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles
UAI 2020
Joint Causal Inference from Multiple Contexts
JMLR 2020
Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias
UAI 2019
Beyond Structural Causal Models: Causal Constraints Models
UAI 2019
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
NIPS 2018
Causal Effect Inference with Deep Latent-Variable Models
NIPS 2017
Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks
JMLR 2016
Ancestral Causal Inference
NIPS 2016
Causal Discovery with Continuous Additive Noise Models
JMLR 2014
On Causal Discovery with Cyclic Additive Noise Models
NIPS 2011
Efficient inference in matrix-variate Gaussian models with \iid observation noise
NIPS 2011
libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models
JMLR 2010
Probabilistic latent variable models for distinguishing between cause and effect
NIPS 2010
Bounds on marginal probability distributions
NIPS 2008
Nonlinear causal discovery with additive noise models
NIPS 2008
Truncating the Loop Series Expansion for Belief Propagation
JMLR 2007
Loop Corrections for Approximate Inference on Factor Graphs
JMLR 2007