| Qmdp-net: Deep learning for planning under partial observability P Karkus, D Hsu, WS Lee Advances in Neural Information Processing Systems, 4694-4704, 2017 | 218 | 2017 |
| Particle Filter Networks with Application to Visual Localization P Karkus, D Hsu, WS Lee 2nd Conference on Robot Learning, 169-178, 2018 | 158 | 2018 |
| Particle Filter Recurrent Neural Networks X Ma, P Karkus, D Hsu, WS Lee arXiv preprint arXiv:1905.12885, 2019 | 125 | 2019 |
| Differentiable slam-net: Learning particle slam for visual navigation P Karkus, S Cai, D Hsu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 84 | 2021 |
| Differentiable algorithm networks for composable robot learning P Karkus, X Ma, D Hsu, LP Kaelbling, WS Lee, T Lozano-Pérez Robotics: Science and Systems, 2019 | 83 | 2019 |
| Diffstack: A differentiable and modular control stack for autonomous vehicles P Karkus, B Ivanovic, S Mannor, M Pavone Conference on robot learning, 2170-2180, 2023 | 79 | 2023 |
| Dtpp: Differentiable joint conditional prediction and cost evaluation for tree policy planning in autonomous driving Z Huang, P Karkus, B Ivanovic, Y Chen, M Pavone, C Lv 2024 IEEE International Conference on Robotics and Automation (ICRA), 6806-6812, 2024 | 58 | 2024 |
| Interactive joint planning for autonomous vehicles Y Chen, S Veer, P Karkus, M Pavone IEEE Robotics and Automation Letters 9 (2), 987-994, 2023 | 51 | 2023 |
| Discriminative particle filter reinforcement learning for complex partial observations X Ma, P Karkus, D Hsu, WS Lee, N Ye arXiv preprint arXiv:2002.09884, 2020 | 48 | 2020 |
| On-chip generation and demultiplexing of quantum correlated photons using a silicon-silica monolithic photonic integration platform N Matsuda, P Karkus, H Nishi, T Tsuchizawa, WJ Munro, H Takesue, ... Optics express 22 (19), 22831-22840, 2014 | 48 | 2014 |
| Tree-structured policy planning with learned behavior models Y Chen, P Karkus, B Ivanovic, X Weng, M Pavone arXiv preprint arXiv:2301.11902, 2023 | 41 | 2023 |
| Closed-loop supervised fine-tuning of tokenized traffic models Z Zhang, P Karkus, M Igl, W Ding, Y Chen, B Ivanovic, M Pavone Proceedings of the Computer Vision and Pattern Recognition Conference, 5422-5432, 2025 | 29 | 2025 |
| Storm: Spatio-temporal reconstruction model for large-scale outdoor scenes J Yang, J Huang, Y Chen, Y Wang, B Li, Y You, A Sharma, M Igl, P Karkus, ... arXiv preprint arXiv:2501.00602, 2024 | 24 | 2024 |
| Distillnerf: Perceiving 3d scenes from single-glance images by distilling neural fields and foundation model features L Wang, SW Kim, J Yang, C Yu, B Ivanovic, S Waslander, Y Wang, ... Advances in Neural Information Processing Systems 37, 62334-62361, 2024 | 20 | 2024 |
| Receding horizon planning with rule hierarchies for autonomous vehicles S Veer, K Leung, R Cosner, Y Chen, P Karkus, M Pavone arXiv preprint arXiv:2212.03323, 2022 | 20 | 2022 |
| Particle filter networks: End-to-end probabilistic localization from visual observations P Karkus, D Hsu, WS Lee arXiv preprint arXiv:1805.08975 2 (6), 8, 2018 | 19 | 2018 |
| Planning with occluded traffic agents using bi-level variational occlusion models F Christianos, P Karkus, B Ivanovic, SV Albrecht, M Pavone arXiv preprint arXiv:2210.14584, 2022 | 18 | 2022 |
| Generation of entangled photons using an arrayed waveguide grating N Matsuda, H Nishi, P Karkus, T Tsuchizawa, K Yamada, WJ Munro, ... Journal of Optics 19 (12), 124005, 2017 | 18 | 2017 |
| Physically embedded planning problems: New challenges for reinforcement learning M Mirza, A Jaegle, JJ Hunt, A Guez, S Tunyasuvunakool, A Muldal, ... arXiv preprint arXiv:2009.05524, 2020 | 16 | 2020 |
| Differentiable mapping networks: Learning structured map representations for sparse visual localization P Karkus, A Angelova, V Vanhoucke, R Jonschkowski 2020 IEEE International Conference on Robotics and Automation (ICRA), 4753-4759, 2020 | 14 | 2020 |
Marco PavoneStanford University and NVIDIAVerified email at stanford.edu
