Benjamin Eckart
Benjamin Eckart
Verified email at nvidia.com
Title
Cited by
Cited by
Year
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
632010
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
602012
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
48*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
442008
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
402016
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
402015
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
352009
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
332018
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
262010
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
192013
Modeling point cloud data using hierarchies of gaussian mixture models
BD Eckart, K Kim, AJ Troccoli, J Kautz
US Patent 10,482,196, 2019
182019
Deepgmr: Learning latent gaussian mixture models for registration
W Yuan, B Eckart, K Kim, V Jampani, D Fox, J Kautz
European Conference on Computer Vision, 733-750, 2020
152020
Fast and Accurate Point Cloud Registration using Trees of Gaussian Mixtures
B Eckart, K Kim, J Kautz
arXiv preprint arXiv:1807.02587, 2018
82018
Compact generative models of point cloud data for 3D perception
B Eckart
Dr. Diss. Carnegie Mellon Univ. Pittsburgh, 2017
82017
Distributed virtual diskless checkpointing: A highly fault tolerant scheme for virtualized clusters
B Eckart, X He, C Wu, F Aderholdt, F Han, S Scott
2012 IEEE 26th International Parallel and Distributed Processing Symposium …, 2012
62012
An extensible i/o performance analysis framework for distributed environments
B Eckart, X He, H Ong, SL Scott
European Conference on Parallel Processing, 57-68, 2009
62009
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
52018
Fast multi-scale point cloud registration with a hierarchical gaussian mixture
BD Eckart, K Kim, J Kautz
US Patent 10,826,786, 2020
12020
A Top-Down Approach to Dynamically Tune I/O for HPC Virtualization
B Eckart, FAJ Yoo, X He, SL Scott
HPCVirt, 2010
12010
Neural Trajectory Fields for Dynamic Novel View Synthesis
C Wang, B Eckart, S Lucey, O Gallo
arXiv preprint arXiv:2105.05994, 2021
2021
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