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2020 – today
- 2023
[c15]Yixuan He, Xitong Zhang, Junjie Huang, Benedek Rozemberczki, Mihai Cucuringu, Gesine Reinert:
PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed Graphs. LoG 2023: 12- [c14]Tyler Derr
, Yao Ma, Benedek Rozemberczki, Neil Shah, Shirui Pan:
The 3rd International Workshop on Machine Learning on Graphs (MLoG). WSDM 2023: 1271-1272 - 2022
- [c13]Benedek Rozemberczki, Anna Gogleva, Sebastian Nilsson, Gavin Edwards, Andriy Nikolov, Eliseo Papa:
MOOMIN: Deep Molecular Omics Network for Anti-Cancer Drug Combination Therapy. CIKM 2022: 3472-3483 - [c12]Benedek Rozemberczki, Stephen Bonner, Andriy Nikolov, Michaël Ughetto, Sebastian Nilsson, Eliseo Papa:
A Unified View of Relational Deep Learning for Drug Pair Scoring. IJCAI 2022: 5564-5571 - [c11]Benedek Rozemberczki, Lauren Watson, Péter Bayer, Hao-Tsung Yang, Oliver Kiss, Sebastian Nilsson, Rik Sarkar:
The Shapley Value in Machine Learning. IJCAI 2022: 5572-5579 - [c10]Benedek Rozemberczki, Charles Tapley Hoyt, Anna Gogleva, Piotr Grabowski, Klas Karis, Andrej Lamov, Andriy Nikolov, Sebastian Nilsson, Michaël Ughetto, Yu Wang, Tyler Derr, Benjamin M. Gyori:
ChemicalX: A Deep Learning Library for Drug Pair Scoring. KDD 2022: 3819-3828 - [i22]Benedek Rozemberczki, Charles Tapley Hoyt, Anna Gogleva, Piotr Grabowski, Klas Karis, Andrej Lamov, Andriy Nikolov, Sebastian Nilsson, Michaël Ughetto, Yu Wang, Tyler Derr, Benjamin M. Gyori:
ChemicalX: A Deep Learning Library for Drug Pair Scoring. CoRR abs/2202.05240 (2022) - [i21]Benedek Rozemberczki, Lauren Watson, Péter Bayer, Hao-Tsung Yang, Oliver Kiss, Sebastian Nilsson, Rik Sarkar:
The Shapley Value in Machine Learning. CoRR abs/2202.05594 (2022) - [i20]Lauren Watson, Abhirup Ghosh, Benedek Rozemberczki, Rik Sarkar:
Continual and Sliding Window Release for Private Empirical Risk Minimization. CoRR abs/2203.03594 (2022) - [i19]Anton Tsitsulin, Benedek Rozemberczki, John Palowitch, Bryan Perozzi:
Synthetic Graph Generation to Benchmark Graph Learning. CoRR abs/2204.01376 (2022) - [i18]Benedek Rozemberczki:
TigerLily: Finding drug interactions in silico with the Graph. CoRR abs/2204.08206 (2022) - [i17]David Geleta, Andriy Nikolov, Mark ODonoghue, Benedek Rozemberczki, Anna Gogleva, Valentina A. M. Tamma, Terry R. Payne:
OntoMerger: An Ontology Integration Library for Deduplicating and Connecting Knowledge Graph Nodes. CoRR abs/2206.02238 (2022) - 2021
- [j2]Benedek Rozemberczki, Carl Allen, Rik Sarkar:
Multi-Scale attributed node embedding. J. Complex Networks 9(2) (2021) - [j1]Ed Fincham, Benedek Rózemberczki, Vitomir Kovanovic, Srecko Joksimovic, Jelena Jovanovic, Dragan Gasevic:
Persistence and Performance in Co-Enrollment Network Embeddings: An Empirical Validation of Tinto's Student Integration Model. IEEE Trans. Learn. Technol. 14(1): 106-121 (2021) - [c9]Benedek Rozemberczki, Rik Sarkar:
The Shapley Value of Classifiers in Ensemble Games. CIKM 2021: 1558-1567 - [c8]Benedek Rozemberczki, Paul Scherer, Yixuan He, George Panagopoulos, Alexander Riedel, Maria Sinziana Astefanoaei, Oliver Kiss, Ferenc Béres, Guzmán López, Nicolas Collignon, Rik Sarkar:
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models. CIKM 2021: 4564-4573 - [c7]Benedek Rozemberczki, Peter Englert, Amol Kapoor, Martin Blais, Bryan Perozzi:
Pathfinder Discovery Networks for Neural Message Passing. WWW 2021: 2547-2558 - [i16]Benedek Rozemberczki, Rik Sarkar:
The Shapley Value of Classifiers in Ensemble Games. CoRR abs/2101.02153 (2021) - [i15]Benedek Rozemberczki, Rik Sarkar:
Twitch Gamers: a Dataset for Evaluating Proximity Preserving and Structural Role-based Node Embeddings. CoRR abs/2101.03091 (2021) - [i14]Benedek Rozemberczki, Paul Scherer, Oliver Kiss, Rik Sarkar, Tamas Ferenci:
Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks. CoRR abs/2102.08100 (2021) - [i13]Benedek Rozemberczki, Paul Scherer, Yixuan He, George Panagopoulos, Maria Sinziana Astefanoaei, Oliver Kiss, Ferenc Béres, Nicolas Collignon, Rik Sarkar:
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models. CoRR abs/2104.07788 (2021) - [i12]Benedek Rozemberczki, Anna Gogleva, Sebastian Nilsson, Gavin Edwards, Andriy Nikolov, Eliseo Papa:
MOOMIN: Deep Molecular Omics Network for Anti-Cancer Drug Combination Therapy. CoRR abs/2110.15087 (2021) - [i11]Benedek Rozemberczki, Stephen Bonner, Andriy Nikolov, Michaël Ughetto, Sebastian Nilsson, Eliseo Papa:
A Unified View of Relational Deep Learning for Drug Pair Scoring. CoRR abs/2111.02916 (2021) - [i10]Gavin Edwards, Sebastian Nilsson, Benedek Rozemberczki, Eliseo Papa:
Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphs. CoRR abs/2111.10625 (2021) - 2020
- [c6]Benedek Rozemberczki, Rik Sarkar:
Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models. CIKM 2020: 1325-1334 - [c5]Benedek Rozemberczki, Oliver Kiss, Rik Sarkar:
Karate Club: An API Oriented Open-Source Python Framework for Unsupervised Learning on Graphs. CIKM 2020: 3125-3132 - [c4]Benedek Rozemberczki, Oliver Kiss, Rik Sarkar:
Little Ball of Fur: A Python Library for Graph Sampling. CIKM 2020: 3133-3140 - [c3]Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann:
Scaling Graph Neural Networks with Approximate PageRank. KDD 2020: 2464-2473 - [i9]Benedek Rozemberczki, Rik Sarkar:
Fast Sequence-Based Embedding with Diffusion Graphs. CoRR abs/2001.07463 (2020) - [i8]Benedek Rozemberczki, Oliver Kiss, Rik Sarkar:
An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs. CoRR abs/2003.04819 (2020) - [i7]Benedek Rozemberczki, Rik Sarkar:
Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models. CoRR abs/2005.07959 (2020) - [i6]Benedek Rozemberczki, Oliver Kiss, Rik Sarkar:
Little Ball of Fur: A Python Library for Graph Sampling. CoRR abs/2006.04311 (2020) - [i5]Lauren Watson, Benedek Rozemberczki, Rik Sarkar:
Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent. CoRR abs/2006.14360 (2020) - [i4]Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann:
Scaling Graph Neural Networks with Approximate PageRank. CoRR abs/2007.01570 (2020) - [i3]Benedek Rozemberczki, Peter Englert, Amol Kapoor, Martin Blais, Bryan Perozzi:
Pathfinder Discovery Networks for Neural Message Passing. CoRR abs/2010.12878 (2020)
2010 – 2019
- 2019
- [c2]Benedek Rozemberczki, Ryan Davies, Rik Sarkar, Charles Sutton:
GEMSEC: graph embedding with self clustering. ASONAM 2019: 65-72 - [i2]Benedek Rozemberczki, Carl Allen, Rik Sarkar:
Multi-scale Attributed Node Embedding. CoRR abs/1909.13021 (2019) - 2018
- [c1]Abhirup Ghosh, Benedek Rozemberczki, Subramanian Ramamoorthy, Rik Sarkar:
Topological signatures for fast mobility analysis. SIGSPATIAL/GIS 2018: 159-168 - [i1]Benedek Rozemberczki, Ryan Davies, Rik Sarkar, Charles Sutton:
GEMSEC: Graph Embedding with Self Clustering. CoRR abs/1802.03997 (2018)
Coauthor Index
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