Emilie Devijver

Orcid: 0000-0002-8360-1834

According to our database1, Emilie Devijver authored at least 25 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Regression tree-based active learning.
Data Min. Knowl. Discov., 2024

On the Fly Detection of Root Causes from Observed Data with Application to IT Systems.
CoRR, 2024

2023
Pool-Based Active Learning with Proper Topological Regions.
CoRR, 2023

Case Studies of Causal Discovery from IT Monitoring Time Series.
CoRR, 2023

Hybrids of Constraint-based and Noise-based Algorithms for Causal Discovery from Time Series.
CoRR, 2023

Survey and Evaluation of Causal Discovery Methods for Time Series (Extended Abstract).
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022
Survey and Evaluation of Causal Discovery Methods for Time Series.
J. Artif. Intell. Res., 2022

A Conditional Mutual Information Estimator for Mixed Data and an Associated Conditional Independence Test.
Entropy, 2022

Entropy-Based Discovery of Summary Causal Graphs in Time Series.
Entropy, 2022

Inferring extended summary causal graphs from observational time series.
CoRR, 2022

Self-Training: A Survey.
CoRR, 2022

Wrapper feature selection with partially labeled data.
Appl. Intell., 2022

Discovery of extended summary graphs in time series.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021
Multi-class Probabilistic Bounds for Self-learning.
CoRR, 2021

Entropy-based Discovery of Summary Causal Graphs in Time Series.
CoRR, 2021

A Mixed Noise and Constraint-Based Approach to Causal Inference in Time Series.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

2020
Prediction regions through Inverse Regression.
J. Mach. Learn. Res., 2020

Smooth And Consistent Probabilistic Regression Trees.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Semi-supervised Wrapper Feature Selection with Imperfect Labels.
CoRR, 2019

Scaling Causal Inference in Additive Noise Models.
Proceedings of the 2019 ACM SIGKDD Workshop on Causal Discovery, 2019

Transductive Bounds for the Multi-Class Majority Vote Classifier.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Dealing with Uncertain Inputs in Regression Trees.
CoRR, 2018

2017
Joint rank and variable selection for parsimonious estimation in a high-dimensional finite mixture regression model.
J. Multivar. Anal., 2017

Model-based regression clustering for high-dimensional data: application to functional data.
Adv. Data Anal. Classif., 2017

2015
Block-diagonal covariance selection for high-dimensional Gaussian graphical models.
CoRR, 2015


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