Casper Kaae Sønderby
Casper Kaae Sønderby, ML/DL Research Scientist
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Cited by
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SignalP 5.0 improves signal peptide predictions using deep neural networks
JJ Almagro Armenteros, KD Tsirigos, CK Sønderby, TN Petersen, ...
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
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
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
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
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
Improved metagenome binning and assembly using deep variational autoencoders
JN Nissen, J Johansen, RL Allesøe, CK Sønderby, JJA Armenteros, ...
Nature biotechnology 39 (5), 555-560, 2021
Convolutional LSTM networks for subcellular localization of proteins
SK Sønderby, CK Sønderby, H Nielsen, O Winther
Algorithms for Computational Biology: Second International Conference, AlCoB …, 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
Deep learning for twelve hour precipitation forecasts
L Espeholt, S Agrawal, C Sønderby, M Kumar, J Heek, C Bromberg, ...
Nature communications 13 (1), 5145, 2022
Diffusion weighted imaging with circularly polarized oscillating gradients
H Lundell, CK Sønderby, TB Dyrby
Magnetic resonance in medicine 73 (3), 1171-1176, 2015
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
Idf++: Analyzing and improving integer discrete flows for lossless compression
R Berg, AA Gritsenko, M Dehghani, CK Sønderby, T Salimans
arXiv preprint arXiv:2006.12459, 2020
Apparent exchange rate imaging in anisotropic systems
CK Sønderby, HM Lundell, LV Søgaard, TB Dyrby
Magnetic resonance in medicine 72 (3), 756-762, 2014
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
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Articles 1–20