Casper Kaae Sønderby
Casper Kaae Sønderby
Research Scientist, Google Brain
Verified email at - Homepage
Cited by
Cited by
SignalP 5.0 improves signal peptide predictions using deep neural networks
JJA Armenteros, KD Tsirigos, CK Sønderby, TN Petersen, O Winther, ...
Nature biotechnology 37 (4), 420-423, 2019
Ladder variational autoencoders
CK Sønderby, T Raiko, L Maaløe, SK Sønderby, O Winther
Neural Information Processing Systems, 2016
DeepLoc: prediction of protein subcellular localization using deep learning
JJ Almagro Armenteros, CK Sønderby, SK Sønderby, H Nielsen, ...
Bioinformatics 33 (21), 3387-3395, 2017
Auxiliary deep generative models
L Maaløe, CK Sønderby, SK Sønderby, O Winther
International conference on machine learning, 1445-1453, 2016
Amortised map inference for image super-resolution
CK Sønderby, J Caballero, L Theis, W Shi, F Huszár
International Conference on Learning Representations (ICLR), 2016
BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis
FO Bagger, D Sasivarevic, SH Sohi, LG Laursen, S Pundhir, CK Sønderby, ...
Nucleic acids research 44 (D1), D917-D924, 2016
NetSurfP‐2.0: Improved prediction of protein structural features by integrated deep learning
MS Klausen, MC Jespersen, H Nielsen, KK Jensen, VI Jurtz, ...
Proteins: Structure, Function, and Bioinformatics 87 (6), 520-527, 2019
Orientationally invariant metrics of apparent compartment eccentricity from double pulsed field gradient diffusion experiments
SN Jespersen, H Lundell, CK Sønderby, TB Dyrby
NMR in Biomedicine 26 (12), 1647-1662, 2013
Convolutional LSTM networks for subcellular localization of proteins
SK Sønderby, CK Sønderby, H Nielsen, O Winther
International Conference on Algorithms for Computational Biology, 68-80, 2015
An introduction to deep learning on biological sequence data: examples and solutions
VI Jurtz, AR Johansen, M Nielsen, JJ Almagro Armenteros, H Nielsen, ...
Bioinformatics 33 (22), 3685-3690, 2017
scVAE: Variational auto-encoders for single-cell gene expression data
CH Grønbech, MF Vording, PN Timshel, CK Sønderby, TH Pers, ...
Bioinformatics 36 (16), 4415-4422, 2020
Recurrent spatial transformer networks
SK Sønderby, CK Sønderby, L Maaløe, O Winther
arXiv preprint arXiv:1509.05329, 2015
Diffusion weighted imaging with circularly polarized oscillating gradients
H Lundell, CK Sønderby, TB Dyrby
Magnetic resonance in medicine 73 (3), 1171-1176, 2015
Metnet: A neural weather model for precipitation forecasting
CK Sønderby, L Espeholt, J Heek, M Dehghani, A Oliver, T Salimans, ...
arXiv preprint arXiv:2003.12140, 2020
Tumor suppressor ASXL1 is essential for the activation of INK4B expression in response to oncogene activity and anti-proliferative signals
X Wu, IH Bekker-Jensen, J Christensen, KD Rasmussen, S Sidoli, Y Qi, ...
Cell research 25 (11), 1205-1218, 2015
Commentary on “Microanisotropy imaging: quantification of microscopic diffusion anisotropy and orientation of order parameter by diffusion MRI with magic-angle spinning of the …
SN Jespersen, H Lundell, CK Sønderby, TB Dyrby
Frontiers in Physics 2, 28, 2014
Apparent exchange rate imaging in anisotropic systems
CK Sønderby, HM Lundell, LV Søgaard, TB Dyrby
Magnetic resonance in medicine 72 (3), 756-762, 2014
Deep recurrent conditional random field network for protein secondary prediction
AR Johansen, CK Sønderby, SK Sønderby, O Winther
Proceedings of the 8th ACM international conference on bioinformatics …, 2017
Improved metagenome binning and assembly using deep variational autoencoders
JN Nissen, J Johansen, RL Allesøe, CK Sønderby, JJA Armenteros, ...
Nature biotechnology, 1-6, 2021
Continuous Relaxation Training of Discrete Latent Variable Image Models
CK Sønderby, B Poole, A Mnih
Bayesian Deeplearning Workshop, Neurips, 2017
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