Jes Frellsen
                                  Jes Frellsen
                                  Associate Professor of Machine Learning and Signal Processing
                                  Section for Cognitive Systems
                                  Department of Applied Mathematics and Computer Science
                                  Technical University of Denmark (DTU)
                                  jbayesebayesfbayesrbayes@bayesdbayestbayesubayes.bayesdbayesk

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                                  I have been an Associate Professor since 2016, and I am currently Associate Professor in Machine Learning and Signal Processing at the Technical University of Denmark (DTU). Before that, I was at the IT University of Copenhagen. Previously I have been a postdoc with Professor Zoubin Ghahramani in the Machine Learning group at the University of Cambridge. Before that, I was a graduate student and postdoc at the Bioinformatics Centre, University of Copenhagen, where I have worked with Professor Anders Krogh and Associate Professor Thomas Hamelryck.

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                                  I work on statistical machine learning with particular interest in:

                                  • Deep Learning
                                  • Deep Generative Models
                                  • Bayesian Modelling and Inference
                                  • Directional Statistics
                                  • Markov chain Monte Carlo methods
                                  • Missing data
                                  • Application in Bioinformatics

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                                  • Simon Bartels (Postdoc, co-supervisor)
                                  • Federico Bergamin (Research Assistant)
                                  • Niels Bruun Ipsen (PhD Student, co-supervisor)
                                  • Philip Stefan Puge Lemaitre (PhD fellow, principal supervisor)

                                  I am also frequently supervising several BSc and MSc thesis students.

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                                  Phone: +45 4525 3923

                                  Building 321, room 015

                                  Postal address:
                                  Technical University of Denmark
                                  Richard Petersens Plads
                                  Building 321, room 015
                                  2800 Kgs. Lyngby
                                  Denmark


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                                  Principal academic appointments

                                  Jul 2022 - Associate Professor
                                  Department of Applied Mathematics and Computer Science, Technical University of Denmark
                                  Aug 2016 -
                                  Jun 2022
                                  Associate Professor
                                  Department of Computer Science, IT University of Copenhagen
                                  May 2013 -
                                  Jun 2016
                                  Postdoctoral researcher with Zoubin Ghahramani
                                  Department of Engineering, University of Cambridge
                                  Dec 2011 -
                                  Apr 2013
                                  Postdoctoral researcher with 墙翻企理网址
                                  Bioinformatics Centre, University of Copenhagen
                                  Mar 2011 -
                                  Aug 2011
                                  墙翻企理网址 with Thomas Hamelryck
                                  Bioinformatics Centre, University of Copenhagen

                                  Other selected appointments

                                  Jul 2022 - Associate Professor (fractional time)
                                  Department of Computer Science, IT University of Copenhagen

                                  Education

                                  2011 PhD in Bioinformatics
                                  Bioinformatics Centre, University of Copenhagen.
                                  "Probabilistic methods in macromolecular structure prediction"
                                  Supervisor: Thomas Hamelryck, co: 企理http
                                  2007 MSc in Bioinformatics, University of Copenhagen
                                  (I was awarded the highest possible grade for my master thesis)
                                  2005 BSc in maths and CS, University of Copenhagen
                                  2004-2005 EAP exchange student at the University of California, Santa Cruz
                                  (worked in Kevin Karplus's Lab group wither and spring)

                                  企理http

                                  Publications

                                  1. Mattei P-A, 企理http (2022) MIWAE: Deep Generative Modelling and Imputation of Incomplete Data. Proceedings of the 36th International Conference on Machine Learning (ICML 2022). Online version, arXiv: 1812.02633
                                  2. Wiqvist S, Mattei P-A, Picchini U, 企理http (2022) Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation. Proceedings of the 36th International Conference on Machine Learning (ICML 2022). Online version, arXiv: 1901.10230
                                  3. Mattei P-A, Frellsen J (2018) Leveraging the Exact Likelihood of Deep Latent Variable Models. Advances in Neural Information Processing Systems 31 (NeurIPS 2018). Online version, arXiv: 1802.04826
                                  4. Mattei P-A, Frellsen J (2018) Refit your Encoder when New Data Comes by. Third workshop on Bayesian Deep Learning (at NeurIPS 2018). Online version
                                  5. Mattei P-A, 企理http (2018) missIWAE: Deep Generative Modelling and Imputation of Incomplete Data. Third workshop on Bayesian Deep Learning (at NeurIPS 2018). Online version
                                  6. Mardia KV, Foldager JI, Frellsen J (2018) Directional Statistics in Protein Bioinformatics. In: Ley C, Verdebout T (eds.), Applied Directional Statistics: Modern Methods and Case Studies. CRC Press. doi:10.1201/9781315228570
                                  7. Boomsma W, Frellsen J (2017) Spherical convolutions and their application in molecular modelling. 机灵企理-最新免费HTTP企理ip软伀_国内专业爬虫socks5 ...:2021-7-5 · 机灵企理主要提供企理IP、企理服务器服务,要更换IP地址的项目均适用,HTTP企理,免费企理ip支持api批量提取ip,企理ip池中的ip可用为广大用户解决IP受限制的问题。 注意: 不提供境外企理IP服务,不得利用本站资源做违法活动。 机灵企理ip产品提供:HTTP企理,免费企理ip,最新企理IP,爬虫企理,Socks5企理 .... 墙翻企理网址. 墙翻企理网址
                                  8. Brouwer T, Frellsen J, Liò P (2017) Comparative Study of Inference Methods for Bayesian Matrix Factorisation. 如何基于http企理解决Java固定ip问题_java_脚本之家:2021-3-25 · 这篇文章主要介绍了如何基于http企理解决Java固定ip问题,文中通过示例企码介绍的非常详细,对大家的学习或者工作具有一定的参考学习企值,需要的朋友可伃参考下. arXiv: 1707.05147
                                  9. Navarro AKW, Frellsen J, Turner RE (2017) The Multivariate Generalised von Mises: Inference and applications. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), 2394-2400. arXiv: 1602.05003
                                  10. Brouwer T, 墙翻企理网址, Liò P (2016) Fast Bayesian non-negative matrix factorisation and tri-factorisation. Advances in Approximate Bayesian Inference Workshop at NeurIPS 2016, Barcelona, Spain. arXiv: 1610.08127
                                  11. Frellsen J, Winther O, Ghahramani Z, Ferkinghoff-Borg J (2016) Bayesian generalised ensemble Markov chain Monte Carlo. Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), Cadiz, Spain. JMLR: W&CP volume 41. [pdf] [supplementary]
                                  12. Hamelryck T, Boomsma W, Ferkinghoff-Borg J, Foldager J, Frellsen J, Haslett J, Theobald D (2015) Proteins, physics and probability kinematics: a Bayesian formulation of the protein folding problem. In: Dryden IL, Kent JT (eds.), Geometry Driven Statistics. Wiley. doi:10.1002/9781118866641.ch18
                                  13. Boomsma W, Tian P, Frellsen J, Jesper Ferkinghoff-Borg, Thomas Hamelryck, Kresten Lindorff-Larsen, and Michele Vendruscolo (2014) Equilibrium simulations of proteins using molecular fragment replacement and NMR chemical shifts. 企理http, 111(38):13852-13857. doi:10.1073/pnas.1404948111
                                  14. Kerpedjiev P*, 企理http*, Lindgreen S, Krogh A (2014) Adaptable probabilistic mapping of short reads using position specific scoring matrices. BMC Bioinformatics 15:100. doi:10.1186/1471-2105-15-100
                                    *Joint first author.
                                  15. Frellsen J*, Menzel P*, Krogh A (2014) Algorithms for mapping high-throughput DNA sequences. In: Brahme A (ed.), Comprehensive Biomedical Physics, Volume 6: Bioinformatics. Elsevier. pp 41-50. doi:10.1016/B978-0-444-53632-7.01103-5.
                                    *Joint first author.
                                  16. 墙翻企理网址, Hamelryck T, Ferkinghoff-Borg J (2013) Combining the multicanonical ensemble with generative probabilistic models of local biomolecular structure. Proceedings 59th ISI World Statistics Congress, pp 139-144, 25-30 August 2013, Hong Kong. International Statistical Institute, The Hague, The Netherlands, December 2013. Online version
                                  17. Menzel P*, 企理http*, Plass M, Rasmussen SH, Krogh A (2013) On the Accuracy of Short Read Mapping. In: Shomron N (ed.), Deep Sequencing Data Analysis, Methods in Molecular Biology. Humana Press. pp. 39-59. doi:10.1007/978-1-62703-514-9_3.
                                    *Joint first author.
                                  18. Olsson S, Frellsen J, Boomsma W, Mardia KV, Hamelryck T (2013) Inference of structure ensembles of flexible biomolecules from sparse, averaged data. PLoS ONE 8(11): e79439. doi:企理http
                                  19. Valentin JB, Andreetta C, Boomsma W, Bottaro S, Ferkinghoff-Borg J, 墙翻企理网址, Mardia KV, Tian P, Hamelryck T (2013) Formulation of probabilistic models of protein structure in atomic detail using the reference ratio method. Proteins 82: 288-299. doi:10.1002/prot.24386
                                  20. Boomsma W, Frellsen J, Harder T, Bottaro S, Johansson KE, et al. (2013) PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structure. 广东远东招标企理有限公司:2021-6-15 · 广东远东招标企理有限公司 地址:广东省广州市越秀区越秀北路222号608-612室 联系电话:020-83642820 网址:www.gdydzb.com 技术支持:广东比比信息技术服务有限公司 … 34(19):1697-1705. doi:10.1002/jcc.23292
                                  21. Hamelryck T, Haslett J, Mardia K, Kent JT, Valentin J, 企理http, Ferkinghoff-Borg J (2013) On the reference ratio method and its application to statistical protein structure prediction. Proceedings of the 32th Leeds Annual Statistical Research Workshop, pp 53-57. Leeds University Press. Online version
                                  22. Frellsen J, Mardia KV, Borg M, Ferkinghoff-Borg J, Thomas Hamelryck (2012) Towards a General Probabilistic Model of Protein Structure: The Reference Ratio Method. Hamelryck T et al. (eds.), Bayesian Methods in Structural Bioinformatics, Statistics for Biology and Health. Springer-Verlag. doi:10.1007/978-3-642-27225-7_4
                                  23. Mardia KV and Frellsen J (2012) Statistics of Bivariate von Mises Distributions. Hamelryck T et al. (eds.), Bayesian Methods in Structural Bioinformatics, Statistics for Biology and Health. Springer-Verlag. doi:10.1007/978-3-642-27225-7_6 [errata]
                                  24. Boomsma W, Frellsen J, and Hamelryck T (2012) Probabilistic Models of Local Biomolecular Structure and Their Applications. Hamelryck T et al. (eds.), Bayesian Methods in Structural Bioinformatics, Statistics for Biology and Health. Springer-Verlag. doi:10.1007/978-3-642-27225-7_10
                                  25. Olsson S, Boomsma W, Frellsen J, Bottaro S, Harder T, Ferkinghoff-Borg J, Hamelryck T (2011) Generative probabilistic models extend the scope of inferential structure determination. Journal of Magnetic Resonance 213(1):182-186. doi:10.1016/j.jmr.2011.08.039
                                  26. Mardia KV, Frellsen J, Borg M, Ferkinghoff-Borg J, Hamelryck T (2011) A statistical view on the reference ratio method. Proceedings of the 30th Leeds Annual Statistical Research Workshop, pp 55-61. Leeds University Press. 企理http
                                  27. Hamelryck T, Borg M, Paluszewski M, Paulsen, Frellsen J, Andreetta C, Boomsma W, Bottaro S, Ferkinghoff-Borg J (2010) Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized. PLoS ONE 5:e13714. doi:10.1371/journal.pone.0013714
                                  28. Harder T, Boomsma W, Paluszewski M, Frellsen J, Johansson KE, Hamelryck T (2010) Beyond rotamers: a generative, probabilistic model of side chains in proteins. BMC Bioinformatics 11:306. doi:10.1186/1471-2105-11-306
                                  29. Borg M, Mardia KV, Boomsma W, Frellsen J, Harder T, Stovgaard K, Ferkinghoff-Borg J, Røgen P, Hamelryck T (2009) A probabilistic approach to protein structure prediction: PHAISTOS in CASP9. The 28th Leeds Annual Statistical Research Workshop, pp 65-70. Leeds University Press. 墙翻企理网址
                                  30. Frellsen J*, Moltke I*, Thiim M, Mardia KV, Ferkinghoff-Borg J, Hamelryck T (2009) A Probabilistic Model of RNA Conformational Space. PLoS Computational Biology 5(6): e1000406. doi:10.1371/journal.pcbi.1000406. *Joint first author.
                                  31. Boomsma W, Borg M, Frellsen J, Harder T, Stovgaard K, Ferkinghoff-Borg J, Krogh A, Mardia KV and Hamelryck, T (2008) PHAISTOS: protein structure prediction using a probabilistic model of local structure. Proceedings of CASP8, pp 82-83. Cagliari, Sardinia, Italy, December 3-7 2008.
                                  32. Marstrand TT, Frellsen J, Moltke I, Thiim M, Valen E, Retelska D, Krogh A (2008) Asap: A Framework for Over-Representation Statistics for Transcription Factor Binding Sites. PLoS ONE 3(2): e1623. doi:10.1371/journal.pone.0001623

                                  Selected talks


                                  Research Group Alumni