Sharp Bounds for Generalized Causal Sensitivity Analysis
D. Frauen, V. Melnychuk, S. Feuerriegel. Accepted at NeurIPS, 2023
Publications
Peer-reviewed
Reliable Off-Policy Learning for Dosage Combinations
J. Schweisthal, D. Frauen, V. Melnychuk, S. Feuerriegel. Accepted at NeurIPS, 2023
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
V. Melnychuk, D. Frauen, S. Feuerriegel. Accepted at NeurIPS, 2023
Normalizing Flows for Interventional Density Estimation
V. Melnychuk, D. Frauen, S. Feuerriegel. Accepted at ICML, 2023
Estimating Average Causal Effects from Patient Trajectories
D. Frauen, T. Hatt, V. Melnychuk, S. Feuerriegel. Accepted at AAAI, 2023
Causal Transformer for Estimating Counterfactual Outcomes
V. Melnychuk, D. Frauen, S. Feuerriegel. Accepted at ICML, 2022
Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned
M. Berrendorf, E. Faerman, V. Melnychuk, V. Tresp, T. Seidl. Accepted at ECIR, 2020
Pre-prints
A Neural Framework for Generalized Causal Sensitivity Analysis
D. Frauen, F. Imrie, A. Curth, V. Melnychuk, S. Feuerriegel, M. van der Schaar. ArXiv preprint, 2023
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation
V. Melnychuk, D. Frauen, S. Feuerriegel. ArXiv preprint, 2023
Counterfactual Fairness for Predictions using Generative Adversarial Networks
Y. Ma, D. Frauen, V. Melnychuk, S. Feuerriegel. ArXiv preprint, 2023
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation
K. Hess, V. Melnychuk, D. Frauen, S. Feuerriegel. ArXiv preprint, 2023
Fair Off-Policy Learning from Observational Data
D. Frauen, V. Melnychuk, S. Feuerriegel. ArXiv preprint, 2023
Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels
V. Melnychuk, E. Faerman, I. Manakov, T. Seidl. ArXiv preprint, 2020
Unsupervised Anomaly Detection for X-Ray Images
D. Davletshina, V. Melnychuk, V. Tran, H. Singla, M. Berrendorf, E. Faerman, M. Fromm, M. Schubert. ArXiv preprint, 2020