| Deepgmr: Learning latent gaussian mixture models for registration W Yuan, B Eckart, K Kim, V Jampani, D Fox, J Kautz Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 217 | 2020 |
| HGMR: Hierarchical Gaussian Mixtures for Adaptive 3D Registration B Eckart, K Kim, J Kautz Proceedings of the European Conference on Computer Vision (ECCV), 705-721, 2018 | 100 | 2018 |
| Accelerated generative models for 3D point cloud data B Eckart, K Kim, A Troccoli, A Kelly, J Kautz Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 79 | 2016 |
| Modeling point cloud data using hierarchies of gaussian mixture models BD Eckart, K Kim, AJ Troccoli, J Kautz US Patent 10,482,196, 2019 | 70 | 2019 |
| An adaptive write buffer management scheme for flash-based ssds G Wu, X He, B Eckart ACM Transactions on Storage (TOS) 8 (1), 1-24, 2012 | 66 | 2012 |
| BPAC: An adaptive write buffer management scheme for flash-based solid state drives G Wu, B Eckart, X He 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST), 1-6, 2010 | 66 | 2010 |
| Self-supervised learning on 3d point clouds by learning discrete generative models B Eckart, W Yuan, C Liu, J Kautz Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 60 | 2021 |
| Performance adaptive UDP for high-speed bulk data transfer over dedicated links B Eckart, X He, Q Wu 2008 IEEE International Symposium on Parallel and Distributed Processing, 1-10, 2008 | 58* | 2008 |
| Failure prediction models for proactive fault tolerance within storage systems B Eckart, X Chen, X He, SL Scott 2008 IEEE International Symposium on Modeling, Analysis and Simulation of …, 2008 | 56 | 2008 |
| Mlmd: Maximum likelihood mixture decoupling for fast and accurate point cloud registration B Eckart, K Kim, A Troccoli, A Kelly, J Kautz 2015 International Conference on 3D Vision, 241-249, 2015 | 52 | 2015 |
| Neural trajectory fields for dynamic novel view synthesis C Wang, B Eckart, S Lucey, O Gallo arXiv preprint arXiv:2105.05994, 2021 | 41 | 2021 |
| A dynamic performance-based flow control method for high-speed data transfer B Eckart, X He, Q Wu, C Xie IEEE Transactions on Parallel and Distributed Systems 21 (1), 114-125, 2009 | 38 | 2009 |
| Fast and Accurate Point Cloud Registration using Trees of Gaussian Mixtures B Eckart, K Kim, J Kautz arXiv preprint arXiv:1807.02587, 2018 | 31 | 2018 |
| Code-m: A non-mds erasure code scheme to support fast recovery from up to two-disk failures in storage systems S Wan, Q Cao, C Xie, B Eckart, X He 2010 IEEE/IFIP International Conference on Dependable Systems & Networks …, 2010 | 27 | 2010 |
| Rem-seg: A robust em algorithm for parallel segmentation and registration of point clouds B Eckart, A Kelly 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013 | 24 | 2013 |
| Hauptspeicherdatenbanken für Unternehmensanwendungen: Datenmanagement für Unternehmensanwendungen im Kontext heutiger Anforderungen und Trends J Krueger, M Grund, C Tinnefeld, B Eckart, A Zeier, H Plattner Datenbank-Spektrum 10 (3), 143-158, 2010 | 16 | 2010 |
| Compact Generative Models of Point Cloud Data for 3D Perception. B Eckart Carnegie Mellon University, USA, 2017 | 14 | 2017 |
| Fast multi-scale point cloud registration with a hierarchical gaussian mixture BD Eckart, K Kim, J Kautz US Patent 10,826,786, 2020 | 12 | 2020 |
| Eoe: Expected overlap estimation over unstructured point cloud data B Eckart, K Kim, K Jan 2018 International Conference on 3D Vision (3DV), 747-755, 2018 | 8 | 2018 |
| An extensible I/O performance analysis framework for distributed environments B Eckart, X He, H Ong, SL Scott Euro-Par 2009 Parallel Processing: 15th International Euro-Par Conference …, 2009 | 6 | 2009 |
