| Approximate bayesian computation M Sunnåker, AG Busetto, E Numminen, J Corander, M Foll, C Dessimoz PLoS computational biology 9 (1), e1002803, 2013 | 753 | 2013 |
| Multifaceted activities of type I interferon are revealed by a receptor antagonist D Levin, WM Schneider, HH Hoffmann, G Yarden, AG Busetto, O Manor, ... Science signaling 7 (327), ra50-ra50, 2014 | 111 | 2014 |
| Unsupervised modeling of cell morphology dynamics for time-lapse microscopy Q Zhong, AG Busetto, JP Fededa, JM Buhmann, DW Gerlich Nature Methods 9 (7), 711-713, 2012 | 83 | 2012 |
| Automatic generation of predictive dynamic models reveals nuclear phosphorylation as the key Msn2 control mechanism M Sunnåker, E Zamora-Sillero, R Dechant, C Ludwig, AG Busetto, ... Science signaling 6 (277), ra41-ra41, 2013 | 59 | 2013 |
| Near-optimal experimental design for model selection in systems biology AG Busetto, A Hauser, G Krummenacher, M Sunnåker, S Dimopoulos, ... Bioinformatics 29 (20), 2625-2632, 2013 | 56 | 2013 |
| Inferring causal metabolic signals that regulate the dynamic TORC 1‐dependent transcriptome AP Oliveira, S Dimopoulos, AG Busetto, S Christen, R Dechant, L Falter, ... Molecular systems biology 11 (4), 802, 2015 | 43 | 2015 |
| Modelling and optimizing mathematics learning in children T Käser, AG Busetto, B Solenthaler, GM Baschera, J Kohn, K Kucian, ... International Journal of Artificial Intelligence in Education 23, 115-135, 2013 | 37 | 2013 |
| Information theoretic model validation for spectral clustering MH Chehreghani, AG Busetto, JM Buhmann Artificial Intelligence and Statistics, 495-503, 2012 | 37 | 2012 |
| Modelling and optimizing the process of learning mathematics T Käser, AG Busetto, GM Baschera, J Kohn, K Kucian, M von Aster, ... Intelligent Tutoring Systems: 11th International Conference, ITS 2012 …, 2012 | 35 | 2012 |
| Stable Bayesian parameter estimation for biological dynamical systems AG Busetto, JM Buhmann 2009 International Conference on Computational Science and Engineering 1 …, 2009 | 29 | 2009 |
| Cluster-based prediction of mathematical learning patterns T Käser, AG Busetto, B Solenthaler, J Kohn, M von Aster, M Gross Artificial Intelligence in Education: 16th International Conference, AIED …, 2013 | 28 | 2013 |
| Optimized expected information gain for nonlinear dynamical systems AG Busetto, CS Ong, JM Buhmann Proceedings of the 26th Annual International Conference on Machine Learning …, 2009 | 24 | 2009 |
| Towards a framework for modelling engagement dynamics in multiple learning domains T Käser, GM Baschera, AG Busetto, S Klingler, B Solenthaler, ... International journal of artificial intelligence in education 22 (1-2), 59-83, 2013 | 18 | 2013 |
| Modeling engagement dynamics in spelling learning GM Baschera, AG Busetto, S Klingler, JM Buhmann, M Gross Artificial Intelligence in Education: 15th International Conference, AIED …, 2011 | 17 | 2011 |
| Structure identification by optimized interventions AG Busetto, J Buhmann Artificial Intelligence and Statistics, 57-64, 2009 | 11 | 2009 |
| Stealth assessment in ITS-a study for developmental dyscalculia S Klingler, T Käser, AG Busetto, B Solenthaler, J Kohn, M von Aster, ... Intelligent Tutoring Systems: 13th International Conference, ITS 2016 …, 2016 | 6 | 2016 |
| Observer design for boolean control networks with unknown inputs C Possieri, A Giovanni Busetto IET Control Theory & Applications 11 (13), 2116-2121, 2017 | 5 | 2017 |
| Pairwise proximity-based features for test escape screening F Lin, CK Hsu, AG Busetto, KT Cheng 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 300-306, 2015 | 5 | 2015 |
| Experimental design for system identification of boolean control networks in biology AG Busetto, J Lygeros 53rd IEEE Conference on Decision and Control, 5704-5709, 2014 | 5 | 2014 |
| Near-optimal selection of parallel inputs in Bayesian experimental design for systems biology AG Busetto, J Lygeros 2014 European Control Conference (ECC), 540-545, 2014 | 3 | 2014 |
Joachim M. BuhmannETH ZurichVerified email at inf.ethz.ch