Valentyn Melnychuk

According to our database, Valentyn Melnychuk authored at least 26 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes.

Emil Javurek, Valentyn Melnychuk, Jonas Schweisthal, Konstantin Hess, Dennis Frauen, Stefan Feuerriegel

CoRR, September, 2025

Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation.

Valentyn Melnychuk, Dennis Frauen, Jonas Schweisthal, Stefan Feuerriegel

CoRR, September, 2025

GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes.

Valentyn Melnychuk, Stefan Feuerriegel

CoRR, September, 2025

Treatment Effect Estimation for Optimal Decision-Making.

Dennis Frauen, Valentyn Melnychuk, Jonas Schweisthal, Mihaela van der Schaar, Stefan Feuerriegel

CoRR, May, 2025

Efficient and Sharp Off-Policy Learning under Unobserved Confounding.

Konstantin Hess, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

CoRR, February, 2025

Orthogonal Representation Learning for Estimating Causal Quantities.

Valentyn Melnychuk, Dennis Frauen, Jonas Schweisthal, Stefan Feuerriegel

CoRR, February, 2025

Differentially private learners for heterogeneous treatment effects.

Maresa Schröder, Valentyn Melnychuk, Stefan Feuerriegel

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Causal machine learning for predicting treatment outcomes.

Stefan Feuerriegel, Dennis Frauen, Valentyn Melnychuk, Jonas Schweisthal, Konstantin Hess, Alicia Curth, Stefan Bauer, Niki Kilbertus, Isaac S. Kohane, Mihaela van der Schaar

CoRR, 2024

Conformal Prediction for Causal Effects of Continuous Treatments.

Maresa Schröder, Dennis Frauen, Jonas Schweisthal, Konstantin Hess, Valentyn Melnychuk, Stefan Feuerriegel

CoRR, 2024

G-Transformer for Conditional Average Potential Outcome Estimation over Time.

Konstantin Hess, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

CoRR, 2024

Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner.

Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

DiffPO: A causal diffusion model for learning distributions of potential outcomes.

Yuchen Ma, Valentyn Melnychuk, Jonas Schweisthal, Stefan Feuerriegel

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Fair Off-Policy Learning from Observational Data.

Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation.

Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation.

Konstantin Hess, Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel

Proceedings of the Twelfth International Conference on Learning Representations, 2024

A Neural Framework for Generalized Causal Sensitivity Analysis.

Dennis Frauen, Fergus Imrie, Alicia Curth, Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Counterfactual Fairness for Predictions using Generative Adversarial Networks.

Yuchen Ma, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

CoRR, 2023

Reliable Off-Policy Learning for Dosage Combinations.

Jonas Schweisthal, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model.

Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Sharp Bounds for Generalized Causal Sensitivity Analysis.

Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Normalizing Flows for Interventional Density Estimation.

Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel

Proceedings of the International Conference on Machine Learning, 2023

Estimating Average Causal Effects from Patient Trajectories.

Dennis Frauen, Tobias Hatt, Valentyn Melnychuk, Stefan Feuerriegel

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Causal Transformer for Estimating Counterfactual Outcomes.

Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel

Proceedings of the International Conference on Machine Learning, 2022

2020

Unsupervised Anomaly Detection for X-Ray Images.

Diana Davletshina, Valentyn Melnychuk, Viet Tran, Hitansh Singla, Max Berrendorf, Evgeniy Faerman, Michael Fromm, Matthias Schubert

CoRR, 2020

Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned.

Max Berrendorf, Evgeniy Faerman, Valentyn Melnychuk, Volker Tresp, Thomas Seidl

Proceedings of the Advances in Information Retrieval, 2020

Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels.

Valentyn Melnychuk, Evgeniy Faerman, Ilja Manakov, Thomas Seidl

Proceedings of the CIKM 2020 Workshops co-located with 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020