Следене
Kaspar Märtens
Kaspar Märtens
Research Scientist at Novo Nordisk
Потвърден имейл адрес: stats.ox.ac.uk - Начална страница
Заглавие
Позовавания
Позовавания
Година
Bayesian statistics and modelling
R van de Schoot, S Depaoli, R King, B Kramer, K Märtens, MG Tadesse, ...
Nature Reviews Methods Primers 1 (1), 1, 2021
6122021
DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns
K Lokk, V Modhukur, B Rajashekar, K Märtens, R Mägi, R Kolde, ...
Genome biology 15, 1-14, 2014
3982014
Predicting quantitative traits from genome and phenome with near perfect accuracy
K Märtens, J Hallin, J Warringer, G Liti, L Parts
Nature communications 7 (1), 11512, 2016
442016
Powerful decomposition of complex traits in a diploid model
J Hallin, K Märtens, AI Young, M Zackrisson, F Salinas, L Parts, ...
Nature Communications 7 (1), 13311, 2016
392016
seqlm: an MDL based method for identifying differentially methylated regions in high density methylation array data
R Kolde, K Märtens, K Lokk, S Laur, J Vilo
Bioinformatics 32 (17), 2604-2610, 2016
322016
BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders
K Märtens, C Yau
International Conference on Artificial Intelligence and Statistics, 2928-2937, 2020
142020
Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models
K Märtens, KR Campbell, C Yau
Proceedings of the 36th International Conference on Machine Learning (ICML), 2019
142019
Erratum to: DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns
K Lokk, V Modhukur, B Rajashekar, K Martens, R Magi, R Kolde, ...
Genome Biol 17 (1), 224, 2016
82016
Neural decomposition: Functional anova with variational autoencoders
K Märtens, C Yau
International Conference on Artificial Intelligence and Statistics, 2917-2927, 2020
62020
629 Salumets A, and Tonisson N
K Lokk, V Modhukur, B Rajashekar, K Martens, R Magi, R Kolde, ...
DNA methylome profiling of human tissues identifies global and 630, 2014
52014
Associations between baseline opioid use disorder severity, mental health and biopsychosocial functioning, with clinical responses to computer-assisted therapy treatment
S Elison-Davies, K Märtens, C Yau, G Davies, J Ward
The American Journal of Drug and Alcohol Abuse 47 (3), 360-372, 2021
32021
Augmented Ensemble MCMC sampling in Factorial Hidden Markov Models
K Märtens, MK Titsias, C Yau
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
32019
Rarity: discovering rare cell populations from single-cell imaging data
K Märtens, M Bortolomeazzi, L Montorsi, J Spencer, F Ciccarelli, C Yau
Bioinformatics 39 (12), btad750, 2023
12023
Enabling feature-level interpretability in non-linear latent variable models: a synthesis of statistical and machine learning techniques
K Martens
University of Oxford, 2019
12019
Disentangling shared and private latent factors in multimodal Variational Autoencoders
K Märtens, C Yau
arXiv preprint arXiv:2403.06338, 2024
2024
Deep Stochastic Processes via Functional Markov Transition Operators
J Xu, E Dupont, K Märtens, T Rainforth, YW Teh
Advances in Neural Information Processing Systems 36, 2024
2024
DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns (vol 15, r54, 2014)
K Lokk, V Modhukur, B Rajashekar, K Martens, R Magi, R Kolde, ...
GENOME BIOLOGY 17, 2016
2016
Enhancing generative perturbation models with LLM-informed gene embeddings
K Märtens, R Donovan-Maiye, J Ferkinghoff-Borg
ICLR 2024 Workshop on Machine Learning for Genomics Explorations, 0
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