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ORCIDJaak Simm
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2020 – today
- 2024
[j16]Wouter Heyndrickx
, Lewis H. Mervin, Tobias Morawietz, Noé Sturm, Lukas Friedrich, Adam Zalewski, Anastasia Pentina, Lina Humbeck, Martijn Oldenhof, Ritsuya Niwayama, Peter Schmidtke, Nikolas Fechner, Jaak Simm, Adam Arany, Nicolas Drizard, Rama Jabal, Arina Afanasyeva, Regis Loeb, Shlok Verma, Simon Harnqvist, Matthew Holmes, Balazs Pejo, Maria Telenczuk, Nicholas Holway, Arne Dieckmann, Nicola Rieke, Friederike Zumsande, Djork-Arné Clevert, Michael Krug, Christopher N. Luscombe, Darren V. S. Green, Peter Ertl, Peter Antal, David Marcus, Nicolas Do Huu, Hideyoshi Fuji, Stephen D. Pickett, Gergely Ács, Eric Boniface, Bernd Beck, Yax Sun, Arnaud Gohier, Friedrich Rippmann, Ola Engkvist, Andreas H. Göller, Yves Moreau, Mathieu N. Galtier, Ansgar Schuffenhauer, Hugo Ceulemans:
MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information. J. Chem. Inf. Model. 64(7): 2331-2344 (2024)- 2023
- [c9]Martijn Oldenhof, Gergely Ács, Balázs Pejó, Ansgar Schuffenhauer, Nicholas Holway, Noé Sturm, Arne Dieckmann, Oliver Fortmeier, Eric Boniface, Clément Mayer, Arnaud Gohier, Peter Schmidtke, Ritsuya Niwayama, Dieter Kopecky, Lewis H. Mervin, Prakash Chandra Rathi, Lukas Friedrich, András Formanek, Peter Antal, Jordon Rahaman, Adam Zalewski, Wouter Heyndrickx, Ezron Oluoch, Manuel Stößel, Michal Vanco, David Endico, Fabien Gelus, Thaïs de Boisfossé, Adrien Darbier, Ashley Nicollet, Matthieu Blottière, Maria Telenczuk, Van Tien Nguyen, Thibaud Martinez, Camille Boillet, Kelvin Moutet, Alexandre Picosson, Aurélien Gasser, Inal Djafar, Antoine Simon, Adam Arany, Jaak Simm, Yves Moreau, Ola Engkvist, Hugo Ceulemans, Camille Marini, Mathieu Galtier:
Industry-Scale Orchestrated Federated Learning for Drug Discovery. AAAI 2023: 15576-15584 - 2022
- [i12]Adam Arany, Jaak Simm, Martijn Oldenhof, Yves Moreau:
SparseChem: Fast and accurate machine learning model for small molecules. CoRR abs/2203.04676 (2022) - [i11]Martijn Oldenhof, Gergely Ács, Balázs Pejó, Ansgar Schuffenhauer, Nicholas Holway, Noé Sturm, Arne Dieckmann, Oliver Fortmeier, Eric Boniface, Clément Mayer, Arnaud Gohier, Peter Schmidtke, Ritsuya Niwayama, Dieter Kopecky, Lewis H. Mervin, Prakash Chandra Rathi, Lukas Friedrich, András Formanek, Peter Antal, Jordon Rahaman, Adam Zalewski, Ezron Oluoch, Manuel Stößel, Michal Vanco, David Endico, Fabien Gelus, Thaïs de Boisfossé, Adrien Darbier, Ashley Nicollet, Matthieu Blottière, Maria Telenczuk, Van Tien Nguyen, Thibaud Martinez, Camille Boillet, Kelvin Moutet, Alexandre Picosson, Aurélien Gasser, Inal Djafar, Adam Arany, Jaak Simm, Yves Moreau, Ola Engkvist, Hugo Ceulemans, Camille Marini, Mathieu Galtier:
Industry-Scale Orchestrated Federated Learning for Drug Discovery. CoRR abs/2210.08871 (2022) - 2021
- [j15]Daniele Raimondi, Jaak Simm, Adam Arany, Yves Moreau:
A novel method for data fusion over entity-relation graphs and its application to protein-protein interaction prediction. Bioinform. 37(16): 2275-2281 (2021) - [j14]Jaak Simm, Lina Humbeck, Adam Zalewski, Noé Sturm, Wouter Heyndrickx, Yves Moreau, Bernd Beck, Ansgar Schuffenhauer:
Splitting chemical structure data sets for federated privacy-preserving machine learning. J. Cheminformatics 13(1): 96 (2021) - [j13]Joris Tavernier, Jaak Simm, Karl Meerbergen, Yves Moreau:
Two-level preconditioning for Ridge Regression. Numer. Linear Algebra Appl. 28(4) (2021) - [c8]Martijn Oldenhof, Adam Arany, Yves Moreau, Jaak Simm:
Self-labeling of Fully Mediating Representations by Graph Alignment. BNAIC/BENELEARN 2021: 46-65 - [c7]Edward De Brouwer, Adam Arany, Jaak Simm, Yves Moreau:
Latent Convergent Cross Mapping. ICLR 2021 - [c6]Jaak Simm, Adam Arany, Edward De Brouwer, Yves Moreau:
Expressive Graph Informer Networks. LOD 2021: 198-212 - [i10]Martijn Oldenhof, Adam Arany, Yves Moreau, Jaak Simm:
Self-Labeling of Fully Mediating Representations by Graph Alignment. CoRR abs/2103.14133 (2021) - 2020
- [j12]Martijn Oldenhof, Adam Arany, Yves Moreau, Jaak Simm:
ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep Learning. J. Chem. Inf. Model. 60(10): 4506-4517 (2020) - [i9]Martijn Oldenhof, Adam Arany, Yves Moreau, Jaak Simm:
ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep Learning. CoRR abs/2002.09914 (2020) - [i8]Joris Tavernier, Jaak Simm, Adam Arany, Karl Meerbergen, Yves Moreau:
Multilevel Gibbs Sampling for Bayesian Regression. CoRR abs/2009.12132 (2020)
2010 – 2019
- 2019
- [j11]Thomas Moerman, Sara Aibar Santos, Carmen Bravo González-Blas, Jaak Simm, Yves Moreau, Jan Aerts, Stein Aerts:
GRNBoost2 and Arboreto: efficient and scalable inference of gene regulatory networks. Bioinform. 35(12): 2159-2161 (2019) - [j10]Joris Tavernier, Jaak Simm, Karl Meerbergen, Jörg Kurt Wegner, Hugo Ceulemans, Yves Moreau:
Fast semi-supervised discriminant analysis for binary classification of large data sets. Pattern Recognit. 91: 86-99 (2019) - [c5]Tom Vander Aa, Imen Chakroun, Tom Ashby, Jaak Simm, Adam Arany, Yves Moreau, Thanh Le Van, José Felipe Golib Dzib, Jörg K. Wegner, Vladimir I. Chupakhin, Hugo Ceulemans, Roel Wuyts, Wilfried Verachtert:
SMURFF: A High-Performance Framework for Matrix Factorization Methods. BNAIC/BENELEARN 2019 - [c4]Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau:
GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series. NeurIPS 2019: 7377-7388 - [i7]Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau:
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series. CoRR abs/1905.12374 (2019) - [i6]Jaak Simm, Adam Arany, Edward De Brouwer, Yves Moreau:
Graph Informer Networks for Molecules. CoRR abs/1907.11318 (2019) - 2018
- [j9]Pooya Zakeri, Jaak Simm, Adam Arany, Sarah ElShal, Yves Moreau:
Gene prioritization using Bayesian matrix factorization with genomic and phenotypic side information. Bioinform. 34(13): i447-i456 (2018) - [j8]Charlotte Bonte, Eleftheria Makri, Amin Ardeshirdavani, Jaak Simm, Yves Moreau, Frederik Vercauteren:
Towards practical privacy-preserving genome-wide association study. BMC Bioinform. 19(1): 537:1-537:12 (2018) - [i5]Joris Tavernier, Jaak Simm, Karl Meerbergen, Yves Moreau:
Multilevel preconditioning for Ridge Regression. CoRR abs/1806.05826 (2018) - [i4]Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau:
Deep Ensemble Tensor Factorization for Longitudinal Patient Trajectories Classification. CoRR abs/1811.10501 (2018) - 2017
- [c3]Jaak Simm, Adam Arany, Pooya Zakeri, Tom Haber, Jörg K. Wegner, Vladimir I. Chupakhin, Hugo Ceulemans, Yves Moreau:
Macau: Scalable Bayesian factorization with high-dimensional side information using MCMC. MLSP 2017: 1-6 - [i3]Joris Tavernier, Jaak Simm, Karl Meerbergen, Jörg K. Wegner, Hugo Ceulemans, Yves Moreau:
Fast semi-supervised discriminant analysis for binary classification of large data-sets. CoRR abs/1709.04794 (2017) - [i2]Charlotte Bonte, Eleftheria Makri, Amin Ardeshirdavani, Jaak Simm, Yves Moreau, Frederik Vercauteren:
Privacy-Preserving Genome-Wide Association Study is Practical. IACR Cryptol. ePrint Arch. 2017: 955 (2017) - 2016
- [c2]Sarah ElShal, Mithila Mathad, Jaak Simm, Jesse Davis, Yves Moreau:
Topic modeling of biomedical text. BIBM 2016: 712-716 - [c1]Sarah ElShal, Jaak Simm, Adam Arany, Pooya Zakeri, Jesse Davis, Yves Moreau:
A Comprehensive Comparison of Two MEDLINE Annotators for Disease and Gene Linkage: Sometimes Less is More. IWBBIO 2016: 765-778 - 2014
- [j7]Jaak Simm, Ildefons Magrans de Abril, Masashi Sugiyama:
Tree-Based Ensemble Multi-Task Learning Method for Classification and Regression. IEICE Trans. Inf. Syst. 97-D(6): 1677-1681 (2014) - [i1]Marc Claesen, Jaak Simm, Dusan Popovic, Yves Moreau, Bart De Moor:
Easy Hyperparameter Search Using Optunity. CoRR abs/1412.1114 (2014) - 2012
- [j6]Jaak Simm, Masashi Sugiyama, Hirotaka Hachiya:
Multi-Task Approach to Reinforcement Learning for Factored-State Markov Decision Problems. IEICE Trans. Inf. Syst. 95-D(10): 2426-2437 (2012) - 2011
- [j5]Makoto Yamada, Masashi Sugiyama, Gordon Wichern, Jaak Simm:
Improving the Accuracy of Least-Squares Probabilistic Classifiers. IEICE Trans. Inf. Syst. 94-D(6): 1337-1340 (2011) - [j4]Jaak Simm, Masashi Sugiyama, Tsuyoshi Kato:
Computationally Efficient Multi-task Learning with Least-squares Probabilistic Classifiers. Inf. Media Technol. 6(2): 508-515 (2011) - [j3]Jaak Simm, Masashi Sugiyama, Tsuyoshi Kato:
Computationally Efficient Multi-task Learning with Least-squares Probabilistic Classifiers. IPSJ Trans. Comput. Vis. Appl. 3: 1-8 (2011) - 2010
- [j2]Makoto Yamada, Masashi Sugiyama, Gordon Wichern, Jaak Simm:
Direct Importance Estimation with a Mixture of Probabilistic Principal Component Analyzers. IEICE Trans. Inf. Syst. 93-D(10): 2846-2849 (2010)
2000 – 2009
- 2008
- [j1]Anni Oja, Jaak Simm:
Knowledge communication in rate.ee, a web picture-rating community. Int. J. Web Based Communities 4(4): 523-538 (2008)
Coauthor Index
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