Jaak Simm

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All published works

Action	Title	Year	Authors
+ PDF Chat	Industry-Scale Orchestrated Federated Learning for Drug Discovery	2023	Martijn Oldenhof Gergely Ács Balázs Pejó Ansgar Schuffenhauer Nicholas Holway Noé Sturm Arne Dieckmann Oliver Fortmeier Eric Boniface Clément Mayer
+ PDF Chat	Self-labeling of Fully Mediating Representations by Graph Alignment	2022	Martijn Oldenhof Ádám Arany Yves Moreau Jaak Simm
+ PDF Chat	Expressive Graph Informer Networks	2022	Jaak Simm Ádám Arany Edward De Brouwer Yves Moreau
+	SparseChem: Fast and accurate machine learning model for small molecules	2022	Ádám Arany Jaak Simm Martijn Oldenhof Yves Moreau
+	Industry-Scale Orchestrated Federated Learning for Drug Discovery	2022	Martijn Oldenhof Gergely Ács Balázs Pejó Ansgar Schuffenhauer Nicholas Holway Noé Sturm Arne Dieckmann Oliver Fortmeier Eric Boniface Clément Mayer
+ PDF Chat	Two‐level preconditioning for Ridge Regression	2021	Joris Tavernier Jaak Simm Karl Meerbergen Yves Moreau
+ PDF Chat	ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep Learning	2020	Martijn Oldenhof Ádám Arany Yves Moreau Jaak Simm
+	Multilevel Gibbs Sampling for Bayesian Regression	2020	Joris Tavernier Jaak Simm Ádám Arany Karl Meerbergen Yves Moreau
+	Graph Informer Networks for Molecules.	2019	Jaak Simm Ádám Arany Edward De Brouwer Yves Moreau
+	Expressive Graph Informer Networks.	2019	Jaak Simm Ádám Arany Edward De Brouwer Yves Moreau
+	SMURFF: a High-Performance Framework for Matrix Factorization	2019	Tom Vander Aa Imen Chakroun Thomas J. Ashby Jaak Simm Ádám Arany Yves Moreau Thanh Le Van José Felipe Golib Dzib Jörg K. Wegner Vladimir Chupakhin
+ PDF Chat	Fast semi-supervised discriminant analysis for binary classification of large data sets	2019	Joris Tavernier Jaak Simm Karl Meerbergen Jörg K. Wegner Hugo Ceulemans Yves Moreau
+	GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series	2019	Edward De Brouwer Jaak Simm Ádám Arany Yves Moreau
+	GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series	2019	Edward De Brouwer Jaak Simm Ádám Arany Yves Moreau
+	SMURFF: a High-Performance Framework for Matrix Factorization	2019	Tom Vander Aa Imen Chakroun Thomas J. Ashby Jaak Simm Ádám Arany Yves Moreau Lê Vǎn Thành José Felipe Golib Dzib Jörg K. Wegner Vladimir Chupakhin
+	Expressive Graph Informer Networks	2019	Jaak Simm Ádám Arany Edward De Brouwer Yves Moreau
+	Multilevel preconditioning for Ridge Regression.	2018	Joris Tavernier Jaak Simm Karl Meerbergen Yves Moreau
+	Deep Ensemble Tensor Factorization for Longitudinal Patient Trajectories Classification	2018	Edward De Brouwer Jaak Simm Ádám Arany Yves Moreau
+	Two-level preconditioning for Ridge Regression	2018	Joris Tavernier Jaak Simm Karl Meerbergen Yves Moreau
+	Highly Scalable Tensor Factorization for Prediction of Drug-Protein Interaction Type	2015	Ádám Arany Jaak Simm Pooya Zakeri Tom Haber Jörg K. Wegner Vladimir Chupakhin Hugo Ceulemans Yves Moreau
+	Macau: Scalable Bayesian Multi-relational Factorization with Side Information using MCMC	2015	Jaak Simm Ádám Arany Pooya Zakeri Tom Haber Jörg K. Wegner Vladimir Chupakhin Hugo Ceulemans Yves Moreau
+	Highly Scalable Tensor Factorization for Prediction of Drug-Protein Interaction Type	2015	Ádám Arany Jaak Simm Pooya Zakeri Tom Haber Jörg K. Wegner Vladimir Chupakhin Hugo Ceulemans Yves Moreau
+	Easy Hyperparameter Search Using Optunity.	2014	Marc Claesen Jaak Simm Dušan Popović Yves Moreau Bart De Moor
+	Easy Hyperparameter Search Using Optunity	2014	Marc Claesen Jaak Simm Dušan Popović Yves Moreau Bart De Moor
+ PDF Chat	Direct Importance Estimation with a Mixture of Probabilistic Principal Component Analyzers	2010	Makoto Yamada Masashi Sugiyama Gordon Wichern Jaak Simm

Common Coauthors

Coauthor	Papers Together
Yves Moreau	24
Ádám Arany	18
Hugo Ceulemans	8
Edward De Brouwer	7
Jörg K. Wegner	6
Joris Tavernier	5
Martijn Oldenhof	5
Vladimir Chupakhin	5
Karl Meerbergen	5
Pooya Zakeri	3
Tom Haber	3
Ashley Nicollet	2
Ezron Oluoch	2
Peter Schmidtke	2
Camille Marini	2
Fabien Gelus	2
Michal Vančo	2
Thaïs De Boisfossé	2
Nicholas Holway	2
Gergely Ács	2
Imen Chakroun	2
Inal Djafar	2
Thomas J. Ashby	2
Arne Dieckmann	2
Matthieu Blottière	2
Balázs Pejó	2
Dieter Kopecky	2
Camille Boillet	2
Jordon Rahaman	2
Ansgar Schuffenhauer	2
Thibaud Martinez	2
Alexandre Picosson	2
David Endico	2
Dušan Popović	2
Mathieu Galtier	2
Manuel Stößel	2
Lewis Mervin	2
Wilfried Verachtert	2
Lukas Friedrich	2
Van Tien Nguyen	2
Eric Boniface	2
José Felipe Golib Dzib	2
Aurélien Gasser	2
Clément Mayer	2
Arnaud Gohier	2
Tom Vander Aa	2
Marc Claesen	2
Adam Zalewski	2
Noé Sturm	2
Adrien Darbier	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares	1982	Christopher C. Paige Michael A. Saunders	3
+ PDF Chat	Identity Mappings in Deep Residual Networks	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	3
+	Pattern Recognition and Machine Learning	2007	Christopher Bishop	3
+ PDF Chat	Adaptive Graph Convolutional Neural Networks	2018	Ruoyu Li Sheng Wang Feiyun Zhu Junzhou Huang	3
+	Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation	2014	Kyunghyun Cho Bart van Merriënboer Çaǧlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio	3
+ PDF Chat	A Sparse Approximate Inverse Preconditioner for the Conjugate Gradient Method	1996	Michele Benzi Carl D. Meyer Miroslav Tůma	2
+	Subspace Preconditioned LSQR for Discrete Ill-Posed Problems	2003	M. Jacobsen Per Christian Hansen Michael A. Saunders	2
+	Multilevel Block Factorization Preconditioners: Matrix-based Analysis and Algorithms for Solving Finite Element Equations	2010	Panayot S. Vassilevski	2
+	Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering	2016	Michaël Defferrard Xavier Bresson Pierre Vandergheynst	2
+	Attention is All you Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	2
+	RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism	2016	Edward Choi Mohammad Taha Bahadori Jimeng Sun Joshua A. Kulas Andy Schuetz Walter F. Stewart	2
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	2
+	Incomplete Cholesky Factorizations with Limited Memory	1999	Chih‐Jen Lin Jorge J. Morè	2
+	Cascadic multilevel methods for ill-posed problems	2009	Lothar Reichel Andriy Shyshkov	2
+ PDF Chat	Recurrent Neural Networks for Multivariate Time Series with Missing Values	2018	Zhengping Che Sanjay Purushotham Kyunghyun Cho David Sontag Yan Liu	2
+ PDF Chat	MoleculeNet: a benchmark for molecular machine learning	2017	Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes Caleb Geniesse Aneesh Pappu Karl Leswing Vijay S. Pande	2
+ PDF Chat	Molecular graph convolutions: moving beyond fingerprints	2016	Steven Kearnes Kevin McCloskey Marc Berndl Vijay S. Pande Patrick Riley	2
+	Inductive Representation Learning on Large Graphs	2017	William L. Hamilton Rex Ying Jure Leskovec	2
+	A multigrid tutorial	1987	William L. Briggs	2
+	Multi-Scale Context Aggregation by Dilated Convolutions	2015	Fisher Yu Vladlen Koltun	2
+	Convolutional Networks on Graphs for Learning Molecular Fingerprints	2015	David Duvenaud Dougal Maclaurin Jorge Aguilera‐Iparraguirre Rafael Gómez‐Bombarelli Timothy Hirzel Alán Aspuru‐Guzik Ryan P. Adams	2
+ PDF Chat	Operator‐based interpolation for bootstrap algebraic multigrid	2010	Thomas A. Manteuffel Steve McCormick M. Park J. Ruge	2
+	The Elements of Statistical Learning	2001	Trevor Hastie J. Friedman Robert Tibshirani	2
+	Flexible Conjugate Gradients	2000	Yvan Notay	2
+	Recursive Krylov‐based multigrid cycles	2007	Yvan Notay Panayot S. Vassilevski	2
+	ILUT: A dual threshold incomplete LU factorization	1994	Yousef Saad	2
+ PDF Chat	Molecular Structure Extraction from Documents Using Deep Learning	2019	Joshua Staker Kyle Marshall Robert Abel Carolyn M. McQuaw	2
+	The Symmetric Eigenvalue Problem	1998	Beresford Ν. Parlett	1
+ PDF Chat	Applied logistic regression	1990	David W. Hosmer Stanley Lemeshow	1
+	Causal diagrams for empirical research	1995	Judea Pearl	1
+	Markov chain Monte Carlo Using an Approximation	2005	J. Andrés Christen Colin Fox	1
+ PDF Chat	Spike and slab variable selection: Frequentist and Bayesian strategies	2005	Hemant Ishwaran J. Sunil Rao	1
+	Spectral Networks and Locally Connected Networks on Graphs	2013	Joan Bruna Wojciech Zaremba Arthur Szlam Yann LeCun	1
+	The block conjugate gradient algorithm and related methods	1980	Dianne P. O’Leary	1
+	Improving predictive inference under covariate shift by weighting the log-likelihood function	2000	Hidetoshi Shimodaira	1
+	Adaptive Smoothed Aggregation ($\alpha$SA) Multigrid	2005	Marian Brezina Robert D. Falgout Scott MacLachlan Thomas A. Manteuffel Steve McCormick J. Ruge	1
+	Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images	1984	Stuart Geman Donald Geman	1
+ PDF Chat	Accurate conjugate gradient methods for families of shifted systems	2004	Jasper van den Eshof Gérard L. G. Sleijpen	1
+ PDF Chat	Optimal Data-Dependent Hashing for Approximate Near Neighbors	2015	Alexandr Andoni Ilya Razenshteyn	1
+	Continuous time bayesian networks	2007	Uri Nodelman Christian R. Shelton Daphne Koller	1
+	Direct and Indirect Effects	2001	Judea Pearl	1
+	Monte Carlo sampling methods using Markov chains and their applications	1970	W. Keith Hastings	1
+	Fast CG-Based Methods for Tikhonov--Phillips Regularization	1999	Andreas Frommer Peter Maaß	1
+ PDF Chat	Complexity analysis of accelerated MCMC methods for Bayesian inversion	2013	Viêt Hà Hòang Christoph Schwab Andrew M. Stuart	1
+	Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients	2011	K. A. Cliffe Michael B. Giles Robert Scheichl Aretha L. Teckentrup	1
+ PDF Chat	No free lunch theorems for optimization	1997	David H. Wolpert William G. Macready	1
+	An empirical evaluation of Bayesian sampling with hybrid Monte Carlo for training neural network classifiers	1999	Dirk Husmeier W.D. Penny Stephen Roberts	1
+ PDF Chat	A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow	2015	Tim Dodwell C. Ketelsen Robert Scheichl Aretha L. Teckentrup	1
+ PDF Chat	Multilevel Monte Carlo Path Simulation	2008	Michael B. Giles	1
+ PDF Chat	Fast unfolding of communities in large networks	2008	Vincent D. Blondel Jean‐Loup Guillaume Renaud Lambiotte Etienne Lefebvre	1