Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Dabiri, Setareh"'
Autor:
Lavington, Jonathan Wilder, Zhang, Ke, Lioutas, Vasileios, Niedoba, Matthew, Liu, Yunpeng, Green, Dylan, Naderiparizi, Saeid, Liang, Xiaoxuan, Dabiri, Setareh, Ścibior, Adam, Zwartsenberg, Berend, Wood, Frank
The training, testing, and deployment, of autonomous vehicles requires realistic and efficient simulators. Moreover, because of the high variability between different problems presented in different autonomous systems, these simulators need to be eas
Externí odkaz:
http://arxiv.org/abs/2405.04491
Autor:
Green, Dylan, Harvey, William, Naderiparizi, Saeid, Niedoba, Matthew, Liu, Yunpeng, Liang, Xiaoxuan, Lavington, Jonathan, Zhang, Ke, Lioutas, Vasileios, Dabiri, Setareh, Scibior, Adam, Zwartsenberg, Berend, Wood, Frank
Current state-of-the-art methods for video inpainting typically rely on optical flow or attention-based approaches to inpaint masked regions by propagating visual information across frames. While such approaches have led to significant progress on st
Externí odkaz:
http://arxiv.org/abs/2405.00251
Autor:
Niedoba, Matthew, Green, Dylan, Naderiparizi, Saeid, Lioutas, Vasileios, Lavington, Jonathan Wilder, Liang, Xiaoxuan, Liu, Yunpeng, Zhang, Ke, Dabiri, Setareh, Ścibior, Adam, Zwartsenberg, Berend, Wood, Frank
Score function estimation is the cornerstone of both training and sampling from diffusion generative models. Despite this fact, the most commonly used estimators are either biased neural network approximations or high variance Monte Carlo estimators
Externí odkaz:
http://arxiv.org/abs/2402.08018
Autor:
Niedoba, Matthew, Lavington, Jonathan Wilder, Liu, Yunpeng, Lioutas, Vasileios, Sefas, Justice, Liang, Xiaoxuan, Green, Dylan, Dabiri, Setareh, Zwartsenberg, Berend, Scibior, Adam, Wood, Frank
Simulation of autonomous vehicle systems requires that simulated traffic participants exhibit diverse and realistic behaviors. The use of prerecorded real-world traffic scenarios in simulation ensures realism but the rarity of safety critical events
Externí odkaz:
http://arxiv.org/abs/2309.12508
Autor:
Dabiri, Setareh, Lioutas, Vasileios, Zwartsenberg, Berend, Liu, Yunpeng, Niedoba, Matthew, Liang, Xiaoxuan, Green, Dylan, Sefas, Justice, Lavington, Jonathan Wilder, Wood, Frank, Scibior, Adam
When training object detection models on synthetic data, it is important to make the distribution of synthetic data as close as possible to the distribution of real data. We investigate specifically the impact of object placement distribution, keepin
Externí odkaz:
http://arxiv.org/abs/2305.14621
Autor:
Liu, Yunpeng, Lioutas, Vasileios, Lavington, Jonathan Wilder, Niedoba, Matthew, Sefas, Justice, Dabiri, Setareh, Green, Dylan, Liang, Xiaoxuan, Zwartsenberg, Berend, Ścibior, Adam, Wood, Frank
Publikováno v:
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
The development of algorithms that learn multi-agent behavioral models using human demonstrations has led to increasingly realistic simulations in the field of autonomous driving. In general, such models learn to jointly predict trajectories for all
Externí odkaz:
http://arxiv.org/abs/2305.11856
Autor:
Zwartsenberg, Berend, Ścibior, Adam, Niedoba, Matthew, Lioutas, Vasileios, Liu, Yunpeng, Sefas, Justice, Dabiri, Setareh, Lavington, Jonathan Wilder, Campbell, Trevor, Wood, Frank
We present a novel, conditional generative probabilistic model of set-valued data with a tractable log density. This model is a continuous normalizing flow governed by permutation equivariant dynamics. These dynamics are driven by a learnable per-set
Externí odkaz:
http://arxiv.org/abs/2206.09021
Autor:
Lioutas, Vasileios, Lavington, Jonathan Wilder, Sefas, Justice, Niedoba, Matthew, Liu, Yunpeng, Zwartsenberg, Berend, Dabiri, Setareh, Wood, Frank, Scibior, Adam
We introduce CriticSMC, a new algorithm for planning as inference built from a composition of sequential Monte Carlo with learned Soft-Q function heuristic factors. These heuristic factors, obtained from parametric approximations of the marginal like
Externí odkaz:
http://arxiv.org/abs/2205.15460
Autor:
Lu, Donghuan, Heisler, Morgan, Ma, Da, Dabiri, Setareh, Lee, Sieun, Ding, Gavin Weiguang, Sarunic, Marinko V., Beg, Mirza Faisal
Optical coherence tomography (OCT) is a non-invasive imaging technology which can provide micrometer-resolution cross-sectional images of the inner structures of the eye. It is widely used for the diagnosis of ophthalmic diseases with retinal alterat
Externí odkaz:
http://arxiv.org/abs/1912.03418
Publikováno v:
In Informatics in Medicine Unlocked 2022 34
