Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Rózemberczki, Benedek"'
Autor:
Geleta, David, Nikolov, Andriy, ODonoghue, Mark, Rozemberczki, Benedek, Gogleva, Anna, Tamma, Valentina, Payne, Terry R.
Duplication of nodes is a common problem encountered when building knowledge graphs (KGs) from heterogeneous datasets, where it is crucial to be able to merge nodes having the same meaning. OntoMerger is a Python ontology integration library whose fu
Externí odkaz:
http://arxiv.org/abs/2206.02238
Autor:
Rozemberczki, Benedek
Tigerlily is a TigerGraph based system designed to solve the drug interaction prediction task. In this machine learning task, we want to predict whether two drugs have an adverse interaction. Our framework allows us to solve this highly relevant real
Externí odkaz:
http://arxiv.org/abs/2204.08206
Graph learning algorithms have attained state-of-the-art performance on many graph analysis tasks such as node classification, link prediction, and clustering. It has, however, become hard to track the field's burgeoning progress. One reason is due t
Externí odkaz:
http://arxiv.org/abs/2204.01376
It is difficult to continually update private machine learning models with new data while maintaining privacy. Data incur increasing privacy loss -- as measured by differential privacy -- when they are used in repeated computations. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2203.03594
Autor:
He, Yixuan, Zhang, Xitong, Huang, Junjie, Rozemberczki, Benedek, Cucuringu, Mihai, Reinert, Gesine
Networks are ubiquitous in many real-world applications (e.g., social networks encoding trust/distrust relationships, correlation networks arising from time series data). While many networks are signed or directed, or both, there is a lack of unified
Externí odkaz:
http://arxiv.org/abs/2202.10793
Autor:
Rozemberczki, Benedek, Watson, Lauren, Bayer, Péter, Yang, Hao-Tsung, Kiss, Olivér, Nilsson, Sebastian, Sarkar, Rik
Over the last few years, the Shapley value, a solution concept from cooperative game theory, has found numerous applications in machine learning. In this paper, we first discuss fundamental concepts of cooperative game theory and axiomatic properties
Externí odkaz:
http://arxiv.org/abs/2202.05594
Autor:
Rozemberczki, Benedek, Hoyt, Charles Tapley, Gogleva, Anna, Grabowski, Piotr, Karis, Klas, Lamov, Andrej, Nikolov, Andriy, Nilsson, Sebastian, Ughetto, Michael, Wang, Yu, Derr, Tyler, Gyori, Benjamin M
In this paper, we introduce ChemicalX, a PyTorch-based deep learning library designed for providing a range of state of the art models to solve the drug pair scoring task. The primary objective of the library is to make deep drug pair scoring models
Externí odkaz:
http://arxiv.org/abs/2202.05240
For Artificial Intelligence to have a greater impact in biology and medicine, it is crucial that recommendations are both accurate and transparent. In other domains, a neurosymbolic approach of multi-hop reasoning on knowledge graphs has been shown t
Externí odkaz:
http://arxiv.org/abs/2111.10625
Autor:
Rozemberczki, Benedek, Bonner, Stephen, Nikolov, Andriy, Ughetto, Michael, Nilsson, Sebastian, Papa, Eliseo
In recent years, numerous machine learning models which attempt to solve polypharmacy side effect identification, drug-drug interaction prediction and combination therapy design tasks have been proposed. Here, we present a unified theoretical view of
Externí odkaz:
http://arxiv.org/abs/2111.02916
Autor:
Rozemberczki, Benedek, Gogleva, Anna, Nilsson, Sebastian, Edwards, Gavin, Nikolov, Andriy, Papa, Eliseo
We propose the molecular omics network (MOOMIN) a multimodal graph neural network used by AstraZeneca oncologists to predict the synergy of drug combinations for cancer treatment. Our model learns drug representations at multiple scales based on a dr
Externí odkaz:
http://arxiv.org/abs/2110.15087