Jeroen Berrevoets

Orcid: 0000-0002-0396-5655

According to our database1, Jeroen Berrevoets authored at least 26 papers between 2019 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Causal Deep Learning: Encouraging Impact on Real-world Problems Through Causality.
Found. Trends Signal Process., 2024

Optimizing Treatment Allocation in the Presence of Interference.
CoRR, 2024

ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

DAGnosis: Localized Identification of Data Inconsistencies using Structures.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
HydaLearn.
Appl. Intell., March, 2023

NOFLITE: Learning to Predict Individual Treatment Effect Distributions.
Trans. Mach. Learn. Res., 2023

Learning continuous-valued treatment effects through representation balancing.
CoRR, 2023

Causal Deep Learning.
CoRR, 2023

AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Representations without Compositional Assumptions.
Proceedings of the International Conference on Machine Learning, 2023

Differentiable and Transportable Structure Learning.
Proceedings of the International Conference on Machine Learning, 2023

GOGGLE: Generative Modelling for Tabular Data by Learning Relational Structure.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

To Impute or not to Impute? Missing Data in Treatment Effect Estimation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Navigating causal deep learning.
CoRR, 2022

Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects.
CoRR, 2022

Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Why you should stop predicting customer churn and start using uplift models.
Inf. Sci., 2021

Autoencoders for strategic decision support.
Decis. Support Syst., 2021

Disentangled Counterfactual Recurrent Networks for Treatment Effect Inference over Time.
CoRR, 2021

DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
HydaLearn: Highly Dynamic Task Weighting for Multi-task Learning with Auxiliary Tasks.
CoRR, 2020

The foundations of cost-sensitive causal classification.
CoRR, 2020

OrganITE: Optimal transplant donor organ offering using an individual treatment effect.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Optimising Individual-Treatment-Effect Using Bandits.
CoRR, 2019

Causal Simulations for Uplift Modeling.
CoRR, 2019


  Loading...