Autonomous vehicle advanced sensing and response B Lakshamanan, LL Hurd, BJ Ashbaugh, E Ould-Ahmed-Vall, L Ma, J Jin, ... US Patent 10,332,320, 2019 | 88 | 2019 |
A block-coordinate descent approach for large-scale sparse inverse covariance estimation E Treister, JS Turek Advances in neural information processing systems 27, 2014 | 44 | 2014 |
On MMSE and MAP denoising under sparse representation modeling over a unitary dictionary JS Turek, I Yavneh, M Elad IEEE Transactions on Signal Processing 59 (8), 3526-3535, 2011 | 41 | 2011 |
Low-dimensional structure in the space of language representations is reflected in brain responses R Antonello, JS Turek, V Vo, A Huth Advances in neural information processing systems 34, 8332-8344, 2021 | 40 | 2021 |
BrainIAK: the brain imaging analysis kit M Kumar, MJ Anderson, JW Antony, C Baldassano, PP Brooks, MB Cai, ... Aperture neuro 1 (4), 2021 | 40 | 2021 |
Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech S Jain, VA Vo, S Mahto, A LeBel, JS Turek, AG Huth NeurIPS 2020, 2020 | 34 | 2020 |
A zero-positive learning approach for diagnosing software performance regressions AM M Alam, J Gottschlich, N Tatbul, JS Turek, T Mattson Advances in Neural Information Processing Systems, 2019 | 34 | 2019 |
Clutter Mitigation in Echocardiography using Sparse Signal Separation JS Turek, I Yavneh, M Elad International Journal on Biomedical Imaging, 2015 | 32 | 2015 |
A convolutional autoencoder for multi-subject fMRI data aggregation PH Chen, X Zhu, H Zhang, JS Turek, J Chen, TL Willke, U Hasson, ... arXiv preprint arXiv:1608.04846, 2016 | 31 | 2016 |
Multi-timescale representation learning in lstm language models S Mahto, VA Vo, JS Turek, AG Huth arXiv preprint arXiv:2009.12727, 2020 | 29 | 2020 |
System and method for acceleration-based vector field maps JF Leon, IJ Alvarez, MS Elli, DIG Aguirre, J Turek US Patent 11,536,574, 2022 | 26 | 2022 |
Targeted rapid knee MRI exam using T2 shuffling JI Tamir, V Taviani, MT Alley, BC Perkins, L Hart, K O'Brien, F Wishah, ... Journal of Magnetic Resonance Imaging 49 (7), e195-e204, 2019 | 23 | 2019 |
Methods and apparatus to automatically generate code for graphical user interfaces JS Turek, JF Leon, LCM Remis, DIG Aguirre, IJ Alvarez, J Gottschlich US Patent 11,061,650, 2021 | 20 | 2021 |
A semi-supervised method for multi-subject FMRI functional alignment JS Turek, TL Willke, PH Chen, PJ Ramadge Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International …, 2017 | 19 | 2017 |
Enabling factor analysis on thousand-subject neuroimaging datasets MJ Anderson, M Capota, JS Turek, X Zhu, TL Willke, Y Wang, PH Chen, ... 2016 IEEE International Conference on Big Data (Big Data), 1151-1160, 2016 | 17 | 2016 |
Capturing shared and individual information in fmri data JS Turek, CT Ellis, LJ Skalaban, NB Turk-Browne, TL Willke 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 16 | 2018 |
On MAP and MMSE estimators for the co-sparse analysis model JS Turek, I Yavneh, M Elad Digital Signal Processing 28, 57-74, 2014 | 16 | 2014 |
A Searchlight Factor Model Approach for Locating Shared Information in Multi-Subject fMRI Analysis H Zhang, PH Chen, J Chen, X Zhu, JS Turek, TL Willke, U Hasson, ... https://arxiv.org/abs/1609.09432, 2016 | 15 | 2016 |
Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network JS Turek, S Jain, V Vo, M Capota, AG Huth, TL Willke International Conference in Machine Learning (ICML), 2020 | 14* | 2020 |
Slower is better: revisiting the forgetting mechanism in LSTM for Slower information decay HYS Chien, JS Turek, N Beckage, VA Vo, CJ Honey, TL Willke arXiv preprint arXiv:2105.05944, 2021 | 13 | 2021 |