An integrated suite of fast docking algorithms E Mashiach, D Schneidman‐Duhovny, A Peri, Y Shavit, R Nussinov, ... Proteins: Structure, Function, and Bioinformatics 78 (15), 3197-3204, 2010 | 143 | 2010 |
Learning multi-scene absolute pose regression with transformers Y Shavit, R Ferens, Y Keller Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 93 | 2021 |
Introduction to camera pose estimation with deep learning Y Shavit, R Ferens arXiv preprint arXiv:1907.05272, 2019 | 72 | 2019 |
Clustergnn: Cluster-based coarse-to-fine graph neural network for efficient feature matching Y Shi, JX Cai, Y Shavit, TJ Mu, W Feng, K Zhang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 65 | 2022 |
Boosting inertial-based human activity recognition with transformers Y Shavit, I Klein IEEE Access 9, 53540-53547, 2021 | 50 | 2021 |
Combining a wavelet change point and the Bayes factor for analysing chromosomal interaction data Y Shavit Molecular BioSystems 10 (6), 1576-1585, 2014 | 43 | 2014 |
FisHiCal: an R package for iterative FISH-based calibration of Hi-C data Y Shavit, FK Hamey, P Lio Bioinformatics 30 (21), 3120-3122, 2014 | 42 | 2014 |
Do we really need scene-specific pose encoders? Y Shavit, R Ferens 2020 25th International Conference on Pattern Recognition (ICPR), 3186-3192, 2021 | 23 | 2021 |
CytoHiC: a cytoscape plugin for visual comparison of Hi-C networks Y Shavit, P Lio' Bioinformatics 29 (9), 1206-1207, 2013 | 23 | 2013 |
Wt-mvsnet: window-based transformers for multi-view stereo J Liao, Y Ding, Y Shavit, D Huang, S Ren, J Guo, W Feng, K Zhang Advances in Neural Information Processing Systems 35, 8564-8576, 2022 | 20 | 2022 |
Camera pose auto-encoders for improving pose regression Y Shavit, Y Keller European Conference on Computer Vision, 140-157, 2022 | 17 | 2022 |
Automated synthesis and analysis of switching gene regulatory networks Y Shavit, B Yordanov, SJ Dunn, CM Wintersteiger, T Otani, Y Hamadi, ... Biosystems 146, 26-34, 2016 | 14 | 2016 |
Paying attention to activation maps in camera pose regression Y Shavit, R Ferens, Y Keller arXiv preprint arXiv:2103.11477, 2021 | 13 | 2021 |
How computer science can help in understanding the 3D genome architecture Y Shavit, I Merelli, L Milanesi, P Lio’ Briefings in bioinformatics 17 (5), 733-744, 2016 | 13 | 2016 |
Hierarchical block matrices as efficient representations of chromosome topologies and their application for 3C data integration Y Shavit, BJ Walker, P Lio’ Bioinformatics 32 (8), 1121-1129, 2016 | 7 | 2016 |
Switching gene regulatory networks Y Shavit, B Yordanov, SJ Dunn, CM Wintersteiger, Y Hamadi, H Kugler Information Processing in Cells and Tissues: 10th International Conference …, 2015 | 4 | 2015 |
Coarse-to-fine multi-scene pose regression with transformers Y Shavit, R Ferens, Y Keller IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 3 | 2023 |
Learning to Localize in Unseen Scenes with Relative Pose Regressors O Idan, Y Shavit, Y Keller arXiv preprint arXiv:2303.02717, 2023 | 1 | 2023 |
Automated detection of fluorescent probes in molecular imaging FK Hamey, Y Shavit, V Maciulyte, C Town, P Liò, S Tosi Computational Intelligence Methods for Bioinformatics and Biostatistics …, 2015 | 1 | 2015 |
Learning single and multi-scene camera pose regression with transformer encoders Y Shavit, R Ferens, Y Keller Computer Vision and Image Understanding 243, 103982, 2024 | | 2024 |