Kaspar Märtens
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K Märtens, C Yau. Neural Decomposition: Functional ANOVA with Variational Autoencoders. Accepted to AISTATS (2020), 2020.

Link to paper Code Slides Video

K Märtens, C Yau. BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders. Accepted to AISTATS (2020), 2020.

Link to paper Code Slides Video

K Märtens, K Campbell, C Yau. Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models. Accepted to ICML (2019), 2019.

Link to paper Code Poster Slides Video

K Märtens, MK Titsias, C Yau. Augmented Ensemble MCMC sampling in Factorial Hidden Markov Models. Accepted to AISTATS (2019), 2019.

Link to paper Code Poster

K Märtens, J Hallin, J Warringer, G Liti, L Parts. Predicting quantitative traits from genome and phenome with near perfect accuracy. In Nature communications (2016), 2016.

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R Kolde*, K Märtens*, K Lokk, S Laur, J Vilo. seqlm: an MDL based method for identifying differentially methylated regions in high density methylation array data. In Bioinformatics (2016), 2016.

Link to paper Code Poster

The source of this webpage is available in https://github.com/kasparmartens/website.

The banner with HMC sampling is based on the implementation of Chi Feng.

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