Kurt De Grave
Katholieke Universiteit Leuven
32 Papers
74 Citations
Kurt De Grave is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Graph kernel & Metagenomics. The author has an hindex of 10, co-authored 29 publications. Previous affiliations of Kurt De Grave include Ghent University & University of Copenhagen Faculty of Science.
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Papers
Predicting human olfactory perception from chemical features of odor molecules
Andreas Keller,Richard C. Gerkin,Yuanfang Guan,Amit Dhurandhar,Gábor Turu,Bence Szalai,Joel D. Mainland,Joel D. Mainland,Yusuke Ihara,Yusuke Ihara,Chung Wen Yu,Russell D. Wolfinger,Celine Vens,Leander Schietgat,Kurt De Grave,Raquel Norel,Gustavo Stolovitzky,Gustavo Stolovitzky,Guillermo A. Cecchi,Leslie B. Vosshall,Leslie B. Vosshall,Pablo Meyer,Pablo Meyer +22 more
TL;DR: Results of a crowdsourcing competition show that it is possible to accurately predict and reverse-engineer the smell of a molecule, with a predictive accuracy that closely approaches a key theoretical limit.
Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases
Kevin Williams,Elizabeth Bilsland,Andrew Sparkes,Wayne Aubrey,Michael Young,Larisa N. Soldatova,Kurt De Grave,Jan Ramon,Michaela de Clare,Worachart Sirawaraporn,Stephen G. Oliver,Ross D. King +11 more
TL;DR: The Robot Scientist ‘Eve’ designed to make drug discovery more economical is reported, demonstrating that the use of AI to select compounds economically outperforms standard drug screening.
Active Learning for High Throughput Screening
Kurt De Grave,Jan Ramon,Luc De Raedt +2 more
- 13 Oct 2008
TL;DR: An algorithm based on Gaussian processes for tackling active k-optimization is developed and evaluated on a challenging set of tasks related to structure-activity relationship prediction.
28
•Proceedings Article
kLog: a language for logical and relational learning with kernels
Paolo Frasconi,Fabrizio Costa,Luc De Raedt,Kurt De Grave +3 more
- 25 Jul 2015
TL;DR: KLog as discussed by the authors is a language for kernel-based learning on expressive logical and relational representations, which allows users to specify logical, relational and relational learning problems declaratively, and can be applied to tackle the same range of tasks that has made statistical relational learning so popular, including classification, regression, multitask learning, and collective classification.
28
•Book
The Dawn of Software Engineering: from Turing to Dijkstra
Edgar G. Daylight,Niklaus Wirth,Tony Hoare,Barbara Liskov,Peter Naur,Kurt De Grave +5 more
- 12 Apr 2012
TL;DR: The Dawn of Software Engineering: from Turing to Dijkstra, Edgar G. Daylight deromanticizes Turing's & logic's role in the history of computing and vividly describes how & why DijkStra's ideas stood out among those of his contemporaries.
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