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2020 – today
- 2021
[j7]Nina Shvetsova
, Bart Bakker, Irina Fedulova, Heinrich Schulz, Dmitry V. Dylov:
Anomaly Detection in Medical Imaging With Deep Perceptual Autoencoders. IEEE Access 9: 118571-118583 (2021)- [c7]Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll:
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. MLMIR@MICCAI 2021: 25-34 - 2020
- [i4]Nina Tuluptceva, Bart Bakker, Irina Fedulova, Heinrich Schulz, Dmitry V. Dylov:
Anomaly Detection with Deep Perceptual Autoencoders. CoRR abs/2006.13265 (2020)
2010 – 2019
- 2019
- [c6]Nina Tuluptceva, Bart Bakker, Irina Fedulova, Anton Konushin:
Perceptual Image Anomaly Detection. ACPR (1) 2019: 164-178 - [i3]Nina Tuluptceva, Bart Bakker, Irina Fedulova, Anton Konushin:
Perceptual Image Anomaly Detection. CoRR abs/1909.05904 (2019) - [i2]Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling:
i-RIM applied to the fastMRI challenge. CoRR abs/1910.08952 (2019) - [i1]Suzanne C. Wetstein, Allison M. Onken, Christina Luffman, Gabrielle M. Baker, Michael E. Pyle, Kevin H. Kensler, Ying Liu, Bart Bakker, Ruud Vlutters, Marinus B. van Leeuwen, Laura C. Collins, Stuart J. Schnitt, Josien P. W. Pluim, Rulla M. Tamimi, Yujing J. Heng, Mitko Veta:
Deep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk. CoRR abs/1911.00036 (2019)
2000 – 2009
- 2008
- [c5]Pieter Horn, Bart Bakker, Gijs Geleijnse, Jan H. M. Korst, Sergei Kurkin:
Determining causal and non-causal relationships in biomedical text by classifying verbs using a Naive Bayesian Classifier. BioNLP 2008: 112-113 - 2007
- [j6]Bart Bakker, Tom Heskes:
Learning and approximate inference in dynamic hierarchical models. Comput. Stat. Data Anal. 52(2): 821-839 (2007) - 2006
- [j5]Hauke Schramm, Xavier L. Aubert, Bart Bakker, Carsten Meyer, Hermann Ney:
Modeling spontaneous speech variability in professional dictation. Speech Commun. 48(5): 493-515 (2006) - 2005
- [c4]Bart Bakker, Carsten Meyer, Xavier L. Aubert:
Fast unsupervised speaker adaptation through a discriminative eigen-MLLR algorithm. INTERSPEECH 2005: 257-260 - 2003
- [j4]Bart Bakker, Tom Heskes:
Task Clustering and Gating for Bayesian Multitask Learning. J. Mach. Learn. Res. 4: 83-99 (2003) - [j3]Tom Heskes, Jan-Joost Spanjers, Bart Bakker, Wim Wiegerinck:
Optimising newspaper sales using neural-Bayesian technology. Neural Comput. Appl. 12(3-4): 212-219 (2003) - [j2]Bart Bakker, Tom Heskes:
Clustering ensembles of neural network models. Neural Networks 16(2): 261-269 (2003) - 2002
- [j1]Tom Heskes, Bart Bakker, Bert Kappen:
Approximate algorithms for neural-Bayesian approaches. Theor. Comput. Sci. 287(1): 219-238 (2002) - [c3]Bart Bakker, Tom Heskes:
Model Clustering for Neural Network Ensembles. ICANN 2002: 383-388 - 2000
- [c2]Bart J. Bakker, Bert Kappen, Tom Heskes:
Survival Analysis: A Neural-Bayesian Approach. ANNIMAB 2000: 162-167
1990 – 1999
- 1999
- [c1]Bart Bakker, Tom Heskes:
Model clustering by deterministic annealing. ESANN 1999: 87-92
Coauthor Index
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