| Dawnbench: An end-to-end deep learning benchmark and competition C Coleman, D Narayanan, D Kang, T Zhao, J Zhang, L Nardi, P Bailis, ... Training 100 (101), 102, 2017 | 323 | 2017 |
| Spatial: A language and compiler for application accelerators D Koeplinger, M Feldman, R Prabhakar, Y Zhang, S Hadjis, R Fiszel, ... Proceedings of the 39th ACM SIGPLAN Conference on Programming Language …, 2018 | 194 | 2018 |
| Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM L Nardi, B Bodin, MZ Zia, J Mawer, A Nisbet, PHJ Kelly, AJ Davison, ... 2015 IEEE international conference on robotics and automation (ICRA), 5783-5790, 2015 | 181 | 2015 |
| Analysis of dawnbench, a time-to-accuracy machine learning performance benchmark C Coleman, D Kang, D Narayanan, L Nardi, T Zhao, J Zhang, P Bailis, ... ACM SIGOPS Operating Systems Review 53 (1), 14-25, 2019 | 107 | 2019 |
| Practical design space exploration L Nardi, D Koeplinger, K Olukotun 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation …, 2019 | 103* | 2019 |
| Efficient octree-based volumetric SLAM supporting signed-distance and occupancy mapping E Vespa, N Nikolov, M Grimm, L Nardi, PHJ Kelly, S Leutenegger IEEE Robotics and Automation Letters 3 (2), 1144-1151, 2018 | 72 | 2018 |
| SLAMBench2: Multi-objective head-to-head benchmarking for visual SLAM B Bodin, H Wagstaff, S Saecdi, L Nardi, E Vespa, J Mawer, A Nisbet, ... 2018 IEEE International Conference on Robotics and Automation (ICRA), 3637-3644, 2018 | 70 | 2018 |
| Integrating algorithmic parameters into benchmarking and design space exploration in 3D scene understanding B Bodin, L Nardi, MZ Zia, H Wagstaff, G Sreekar Shenoy, M Emani, ... Proceedings of the 2016 International Conference on Parallel Architectures …, 2016 | 61 | 2016 |
| A numbering algorithm for finite element on extruded meshes which avoids the unstructured mesh penalty GT Bercea, ATT McRae, DA Ham, L Mitchell, F Rathgeber, L Nardi, ... preprint, arxiv. org/abs/1604.05937 [cs. MS], 2016 | 50* | 2016 |
| Navigating the landscape for real-time localization and mapping for robotics and virtual and augmented reality S Saeedi, B Bodin, H Wagstaff, A Nisbet, L Nardi, J Mawer, N Melot, ... Proceedings of the IEEE 106 (11), 2020-2039, 2018 | 46 | 2018 |
| Comparative Design Space Exploration of Dense and Semi-Dense SLAM MZ Zia, L Nardi, A Jack, E Vespa, B Bodin, PHJ Kelly, AJ Davison International Conference on Robotics and Automation (ICRA), 2016 | 39 | 2016 |
| Application-oriented design space exploration for SLAM algorithms S Saeedi, L Nardi, E Johns, B Bodin, PHJ Kelly, AJ Davison 2017 IEEE International Conference on Robotics and Automation (ICRA), 5716-5723, 2017 | 36 | 2017 |
| Bayesian optimization with a prior for the optimum A Souza, L Nardi, LB Oliveira, K Olukotun, M Lindauer, F Hutter Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 33* | 2021 |
| YAO: a software for variational data assimilation using numerical models L Nardi, C Sorror, F Badran, S Thiria Computational Science and Its Applications–ICCSA 2009: International …, 2009 | 31 | 2009 |
| Algorithmic performance-accuracy trade-off in 3d vision applications using hypermapper L Nardi, B Bodin, S Saeedi, E Vespa, AJ Davison, PHJ Kelly 2017 IEEE International Parallel and Distributed Processing Symposium …, 2017 | 27 | 2017 |
| BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization C Hvarfner, D Stoll, A Souza, M Lindauer, F Hutter, L Nardi arXiv preprint arXiv:2204.11051, 2022 | 20 | 2022 |
| Learning of parameters in behavior trees for movement skills M Mayr, K Chatzilygeroudis, F Ahmad, L Nardi, V Krueger 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 13 | 2021 |
| LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso L Nardi, A Gramfort, J Salmon, K Sehic 1st International Conference on Automated Machine Learning (AutoML), 2022 | 11* | 2022 |
| Joint entropy search for maximally-informed Bayesian optimization C Hvarfner, F Hutter, L Nardi arXiv preprint arXiv:2206.04771, 2022 | 9 | 2022 |
| DeepFreak: Learning crystallography diffraction patterns with automated machine learning A Souza, LB Oliveira, S Hollatz, M Feldman, K Olukotun, JM Holton, ... arXiv preprint arXiv:1904.11834, 2019 | 9 | 2019 |
Kunle OlukotunCadence Design Systems Professor of Computer Science, Stanford UniversityVerified email at stanford.edu
