Jes Frellsen
Title
Cited by
Cited by
Year
A probabilistic model of RNA conformational space
J Frellsen, I Moltke, M Thiim, KV Mardia, J Ferkinghoff-Borg, T Hamelryck
PLoS computational biology 5 (6), e1000406, 2009
1132009
Potentials of mean force for protein structure prediction vindicated, formalized and generalized
T Hamelryck, M Borg, M Paluszewski, J Paulsen, J Frellsen, C Andreetta, ...
PloS one 5 (11), e13714, 2010
832010
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets
PA Mattei, J Frellsen
Proceedings of the 36th International Conference on Machine Learning, PMLR …, 2019
742019
Beyond rotamers: a generative, probabilistic model of side chains in proteins
T Harder, W Boomsma, M Paluszewski, J Frellsen, KE Johansson, ...
BMC bioinformatics 11 (1), 1-13, 2010
722010
Spherical convolutions and their application in molecular modelling.
W Boomsma, J Frellsen
Advances in Neural Information Processing Systems 30 (NeurIPS 2017) 2, 6, 2017
562017
Adaptable probabilistic mapping of short reads using position specific scoring matrices
P Kerpedjiev, J Frellsen, S Lindgreen, A Krogh
BMC bioinformatics 15 (1), 1-17, 2014
502014
Inference of structure ensembles of flexible biomolecules from sparse, averaged data
S Olsson, J Frellsen, W Boomsma, KV Mardia, T Hamelryck
PloS one 8 (11), e79439, 2013
492013
Asap: a framework for over-representation statistics for transcription factor binding sites
TT Marstrand, J Frellsen, I Moltke, M Thiim, E Valen, D Retelska, A Krogh
PLoS One 3 (2), e1623, 2008
442008
PHAISTOS: a framework for Markov chain Monte Carlo simulation and inference of protein structure
W Boomsma, J Frellsen, T Harder, S Bottaro, KE Johansson, P Tian, ...
Journal of computational chemistry 34 (19), 1697-1705, 2013
402013
Leveraging the exact likelihood of deep latent variable models
PA Mattei, J Frellsen
Advances in Neural Information Processing Systems 31 (NeurIPS 2018), 2018
292018
Equilibrium simulations of proteins using molecular fragment replacement and NMR chemical shifts
W Boomsma, P Tian, J Frellsen, J Ferkinghoff-Borg, T Hamelryck, ...
Proceedings of the National Academy of Sciences 111 (38), 13852-13857, 2014
272014
Generative probabilistic models extend the scope of inferential structure determination
S Olsson, W Boomsma, J Frellsen, S Bottaro, T Harder, J Ferkinghoff-Borg, ...
Journal of Magnetic Resonance 213 (1), 182-186, 2011
232011
The Multivariate Generalised von Mises Distribution: Inference and Applications
AKW Navarro, J Frellsen, RE Turner
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence …, 2017
19*2017
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
S Wiqvist, M Pierre-Alexandre, U Picchini, J Frellsen
Proceedings of the 36th International Conference on Machine Learning, PMLR …, 2019
142019
Statistics of Bivariate von Mises Distributions
KV Mardia, J Frellsen
Bayesian Methods in Structural Bioinformatics, 159-178, 2012
112012
Comparative study of inference methods for Bayesian nonnegative matrix factorisation
T Brouwer, J Frellsen, P Lió
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
102017
Formulation of probabilistic models of protein structure in atomic detail using the reference ratio method
JB Valentin, C Andreetta, W Boomsma, S Bottaro, J Ferkinghoff‐Borg, ...
Proteins: Structure, Function, and Bioinformatics 82 (2), 288-299, 2014
102014
Bayesian generalised ensemble markov chain monte carlo
J Frellsen, O Winther, Z Ghahramani, J Ferkinghoff-Borg
Artificial Intelligence and Statistics, 408-416, 2016
92016
Towards a General Probabilistic Model of Protein Structure: The Reference Ratio Method
J Frellsen, KV Mardia, M Borg, J Ferkinghoff-Borg, T Hamelryck
Bayesian Methods in Structural Bioinformatics, 125-134, 2012
82012
On the accuracy of short read mapping
P Menzel, J Frellsen, M Plass, SH Rasmussen, A Krogh
Deep Sequencing Data Analysis, 39-59, 2013
72013
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Articles 1–20