Search Results for author: Valentyn Melnychuk

Found 5 papers, 4 papers with code

Causal Transformer for Estimating Counterfactual Outcomes

1 code implementation14 Apr 2022 Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel

In this paper, we develop a novel Causal Transformer for estimating counterfactual outcomes over time.

Estimating average causal effects from patient trajectories

no code implementations2 Mar 2022 Dennis Frauen, Tobias Hatt, Valentyn Melnychuk, Stefan Feuerriegel

Instead, medical practice is increasingly interested in estimating causal effects among patient subgroups from electronic health records, that is, observational data.

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

1 code implementation23 Oct 2020 Valentyn Melnychuk, Evgeniy Faerman, Ilja Manakov, Thomas Seidl

Furthermore, our experiments show that exponential moving average (EMA) of model parameters, which is a component of both algorithms, is not needed for our classification problem, as disabling it leaves the outcome unchanged.

Retinal OCT Disease Classification Semi-Supervised Image Classification +1

Unsupervised Anomaly Detection for X-Ray Images

1 code implementation29 Jan 2020 Diana Davletshina, Valentyn Melnychuk, Viet Tran, Hitansh Singla, Max Berrendorf, Evgeniy Faerman, Michael Fromm, Matthias Schubert

Therefore, we adopt state-of-the-art approaches for unsupervised learning to detect anomalies and show how the outputs of these methods can be explained.

Unsupervised Anomaly Detection

Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned

1 code implementation19 Nov 2019 Max Berrendorf, Evgeniy Faerman, Valentyn Melnychuk, Volker Tresp, Thomas Seidl

In this work, we focus on the problem of entity alignment in Knowledge Graphs (KG) and we report on our experiences when applying a Graph Convolutional Network (GCN) based model for this task.

Entity Alignment Knowledge Graphs

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