Krzysztof J. Geras
Cytowane przez
Cytowane przez
Do Deep Convolutional Nets Really Need to be Deep (Or Even Convolutional)?
G Urban, KJ Geras, S Ebrahimi Kahou, O Aslan, S Wang, R Caruana, ...
arXiv preprint arXiv:1603.05691, 2016
fastMRI: An open dataset and benchmarks for accelerated MRI
J Zbontar, F Knoll, A Sriram, MJ Muckley, M Bruno, A Defazio, M Parente, ...
arXiv preprint arXiv:1811.08839, 2018
High-resolution breast cancer screening with multi-view deep convolutional neural networks
KJ Geras, S Wolfson, Y Shen, N Wu, S Kim, E Kim, L Heacock, U Parikh, ...
arXiv preprint arXiv:1703.07047, 2017
Deep neural networks improve radiologists’ performance in breast cancer screening
N Wu, J Phang, J Park, Y Shen, Z Huang, M Zorin, S Jastrzębski, T Févry, ...
IEEE transactions on medical imaging 39 (4), 1184-1194, 2019
Blending LSTMs into CNNs
KJ Geras, A Mohamed, R Caruana, G Urban, S Wang, O Aslan, ...
arXiv preprint arXiv:1511.06433, 2015
Scheduled denoising autoencoders
KJ Geras, C Sutton
arXiv preprint arXiv:1406.3269, 2014
Artificial intelligence for mammography and digital breast tomosynthesis: current concepts and future perspectives
KJ Geras, RM Mann, L Moy
Radiology 293 (2), 246-259, 2019
Breast density classification with deep convolutional neural networks
N Wu, KJ Geras, Y Shen, J Su, SG Kim, E Kim, S Wolfson, L Moy, K Cho
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
New frontiers: an update on computer-aided diagnosis for breast imaging in the age of artificial intelligence
Y Gao, KJ Geras, AA Lewin, L Moy
American Journal of Roentgenology 212 (2), 300-307, 2019
Analysis of deep neural networks with extended data jacobian matrix
S Wang, A Mohamed, R Caruana, J Bilmes, M Plilipose, M Richardson, ...
International Conference on Machine Learning, 718-726, 2016
Isoelastic agents and wealth updates in machine learning markets
J Millin, K Geras, AJ Storkey
Proceedings of the 29th International Conference on Machine Learning (ICML …, 2012
Machine learning in breast MRI
B Reig, L Heacock, KJ Geras, L Moy
Journal of Magnetic Resonance Imaging 52 (4), 998-1018, 2020
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms
T Schaffter, DSM Buist, CI Lee, Y Nikulin, D Ribli, Y Guan, W Lotter, Z Jie, ...
JAMA network open 3 (3), e200265-e200265, 2020
Multiple-source cross-validation
K Geras, C Sutton
International Conference on Machine Learning, 1292-1300, 2013
Joint model training
O Aslan, R Caruana, MR Richardson, A Mohamed, M Philipose, K Geras, ...
US Patent App. 15/195,894, 2017
fastmri: A publicly available raw k-space and dicom dataset of knee images for accelerated mr image reconstruction using machine learning
F Knoll, J Zbontar, A Sriram, MJ Muckley, M Bruno, A Defazio, M Parente, ...
Radiology: Artificial Intelligence 2 (1), e190007, 2020
Classifier-agnostic saliency map extraction
K Żołna, KJ Geras, K Cho
Computer Vision and Image Understanding, 102969, 2020
The break-even point on optimization trajectories of deep neural networks
S Jastrzebski, M Szymczak, S Fort, D Arpit, J Tabor, K Cho, K Geras
arXiv preprint arXiv:2002.09572, 2020
Globally-aware multiple instance classifier for breast cancer screening
Y Shen, N Wu, J Phang, J Park, G Kim, L Moy, K Cho, KJ Geras
International Workshop on Machine Learning in Medical Imaging, 18-26, 2019
The NYU breast cancer screening dataset V1. 0
N Wu, J Phang, J Park, Y Shen, SG Kim, L Heacock, L Moy, K Cho, ...
New York Univ., New York, NY, USA, Tech. Rep, 2019
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