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Juho Timonen
Doctoral Candidate Aalto University, Department of Computer Science
Programming and applied mathematics.

I am a doctoral student in the Computational Systems Biology group. My research topics and interests include:

  • General probabilistic and deep generative models
  • Gaussian processes with both categorical and continuous input variables
  • Reliable and efficient usage of numerical solvers in probabilistic models
  • Dynamic modeling of single cell RNA-seq data
  • Molecular network inference

My hobbies include cycling and cross-country skiing. See my Strava profile.

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Publications

  • J Timonen, N Siccha, B Bales, H Lähdesmäki and A Vehtari. An importance sampling approach for reliable and efficient inference in Bayesian ordinary differential equation models. arXiv:2205.09059 (2022). url

  • J Timonen and H Lähdesmäki. Scalable Mixed-domain Gaussian Processes. arXiv:2111.02019 (2021). url

  • J Timonen, H Mannerström, A Vehtari and H Lähdesmäki. lgpr: an interpretable non-parametric method for inferring covariate effects from longitudinal data. Bioinformatics (2021). url

  • J Timonen, H Mannerström, H Lähdesmäki and J Intosalmi. A Probabilistic Framework for Molecular Network Structure Inference by Means of Mechanistic Modeling. IEEE/ACM Transactions on Computational Biology and Bioinformatics (2018). url

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Software

See my Github page for more.