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Evgheniy Faerman
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2020 – today
- 2023
- [c15]Michael Fromm, Max Berrendorf, Evgeniy Faerman, Thomas Seidl:
Cross-Domain Argument Quality Estimation. ACL (Findings) 2023: 13435-13448 - 2022
- [i15]Michael Fromm, Max Berrendorf, Johanna Reiml, Isabelle Mayerhofer, Siddharth Bhargava, Evgeniy Faerman, Thomas Seidl:
Towards a Holistic View on Argument Quality Prediction. CoRR abs/2205.09803 (2022) - 2021
- [b1]Evgeniy Faerman:
Representation learning on relational data. Ludwig Maximilian University of Munich, Germany, 2021 - [c14]Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi, Yao Zhang, Lukas Dennert, Sophia Selle, Yang Mao, Thomas Seidl:
Argument Mining Driven Analysis of Peer-Reviews. AAAI 2021: 4758-4766 - [c13]Max Berrendorf
, Ludwig Wacker, Evgeniy Faerman:
A Critical Assessment of State-of-the-Art in Entity Alignment. ECIR (2) 2021: 18-32 - [c12]Max Berrendorf, Evgeniy Faerman, Volker Tresp:
Active Learning for Entity Alignment. ECIR (1) 2021: 48-62 - [c11]Michael Fromm, Max Berrendorf, Sandra Obermeier, Thomas Seidl, Evgeniy Faerman:
Diversity Aware Relevance Learning for Argument Search. ECIR (2) 2021: 264-271 - [i14]Elena A. Kronberg, Tanveer Hannan, Jens Huthmacher, Marcus Münzer, Florian Peste, Ziyang Zhou, Max Berrendorf, Evgeniy Faerman, Fabio Gastaldello, Simona Ghizzardi
Prediction of soft proton intensities in the near-Earth space using machine learning. CoRR abs/2105.15108 (2021) - [i13]Nataliia Kees, Michael Fromm, Evgeniy Faerman, Thomas Seidl:
Active Learning for Argument Strength Estimation. CoRR abs/2109.11319 (2021) - 2020
- [c10]Valentyn Melnychuk, Evgeniy Faerman, Ilja Manakov, Thomas Seidl:
Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels. CIKM (Workshops) 2020 - [c9]Max Berrendorf
Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned. ECIR (2) 2020: 3-11 - [c8]Evgeniy Faerman, Felix Borutta, Julian Busch, Matthias Schubert:
Ada-LLD: Adaptive Node Similarity Using Multi-Scale Local Label Distributions. WI/IAT 2020: 25-32 - [c7]Max Berrendorf
Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods. WI/IAT 2020: 371-374 - [d1]Michael Fromm
Argument Mining Driven Analysis of Peer-Reviews Dataset. Zenodo, 2020 - [i12]Max Berrendorf
Active Learning for Entity Alignment. CoRR abs/2001.08943 (2020) - [i11]Diana Davletshina, Valentyn Melnychuk
Unsupervised Anomaly Detection for X-Ray Images. CoRR abs/2001.10883 (2020) - [i10]Max Berrendorf
Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods with Adjusted Mean Rank. CoRR abs/2002.06914 (2020) - [i9]Julian Busch, Evgeniy Faerman, Matthias Schubert, Thomas Seidl:
Learning Self-Expression Metrics for Scalable and Inductive Subspace Clustering. CoRR abs/2009.12875 (2020) - [i8]Valentyn Melnychuk
Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels. CoRR abs/2010.12316 (2020) - [i7]Max Berrendorf, Ludwig Wacker, Evgeniy Faerman:
A Critical Assessment of State-of-the-Art in Entity Alignment. CoRR abs/2010.16314 (2020) - [i6]Michael Fromm, Max Berrendorf, Sandra Obermeier, Thomas Seidl, Evgeniy Faerman:
Diversity Aware Relevance Learning for Argument Search. CoRR abs/2011.02177 (2020) - [i5]Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi, Yao Zhang, Lukas Dennert, Sophia Selle, Yang Mao, Thomas Seidl:
Argument Mining Driven Analysis of Peer-Reviews. CoRR abs/2012.07743 (2020)
2010 – 2019
- 2019
- [c6]Evgeniy Faerman, Manuell Rogalla, Niklas Strauß, Adrian Krüger, Benedict Blümel
Spatial Interpolation with Message Passing Framework. ICDM Workshops 2019: 135-141 - [c5]Michael Fromm, Max Berrendorf
XD-STOD: Cross-Domain Superresolution for Tiny Object Detection. ICDM Workshops 2019: 142-148 - [c4]Felix Borutta, Julian Busch, Evgeniy Faerman, Adina Klink, Matthias Schubert:
Structural Graph Representations based on Multiscale Local Network Topologies. WI 2019: 91-98 - [c3]Michael Fromm, Evgeniy Faerman, Thomas Seidl
TACAM: Topic And Context Aware Argument Mining. WI 2019: 99-106 - [i4]Michael Fromm, Evgeniy Faerman, Thomas Seidl:
TACAM: Topic And Context Aware Argument Mining. CoRR abs/1906.00923 (2019) - [i3]Max Berrendorf
Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned. CoRR abs/1911.08342 (2019) - 2018
- [c2]Evgheniy Faerman, Felix Borutta, Kimon Fountoulakis, Michael W. Mahoney:
LASAGNE: Locality and Structure Aware Graph Node Embedding. WI 2018: 246-253 - [i2]Evgheniy Faerman, Felix Borutta, Julian Busch, Matthias Schubert:
Semi-Supervised Learning on Graphs Based on Local Label Distributions. CoRR abs/1802.05563 (2018) - 2017
- [c1]Erik Seglem, Andreas Züfle, Jan Stutzki, Felix Borutta, Evgheniy Faerman, Matthias Schubert:
On Privacy in Spatio-Temporal Data: User Identification Using Microblog Data. SSTD 2017: 43-61 - [i1]Evgheniy Faerman, Felix Borutta, Kimon Fountoulakis, Michael W. Mahoney:
LASAGNE: Locality And Structure Aware Graph Node Embedding. CoRR abs/1710.06520 (2017)
Coauthor Index
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