Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Schrum, Mariah"'
Adaptive brain stimulation can treat neurological conditions such as Parkinson's disease and post-stroke motor deficits by influencing abnormal neural activity. Because of patient heterogeneity, each patient requires a unique stimulation policy to ac
Externí odkaz:
http://arxiv.org/abs/2406.06714
When querying a large language model (LLM), the context, i.e. personal, demographic, and cultural information specific to an end-user, can significantly shape the response of the LLM. For example, asking the model to explain Newton's second law with
Externí odkaz:
http://arxiv.org/abs/2405.01768
Autor:
Lee, Kin Man, Krishna, Arjun, Zaidi, Zulfiqar, Paleja, Rohan, Chen, Letian, Hedlund-Botti, Erin, Schrum, Mariah, Gombolay, Matthew
Publikováno v:
HRI '23: Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
As high-speed, agile robots become more commonplace, these robots will have the potential to better aid and collaborate with humans. However, due to the increased agility and functionality of these robots, close collaboration with humans can create s
Externí odkaz:
http://arxiv.org/abs/2304.03756
Personalization of autonomous vehicles (AV) may significantly increase trust, use, and acceptance. In particular, we hypothesize that the similarity of an AV's driving style compared to the end-user's driving style will have a major impact on end-use
Externí odkaz:
http://arxiv.org/abs/2301.08595
Learning from demonstration (LfD) techniques seek to enable novice users to teach robots novel tasks in the real world. However, prior work has shown that robot-centric LfD approaches, such as Dataset Aggregation (DAgger), do not perform well with hu
Externí odkaz:
http://arxiv.org/abs/2110.03134
Autor:
Schrum, Mariah L., Connolly, Mark, Cole, Eric, Ghetiya, Mihir, Gross, Robert, Gombolay, Matthew C.
Learning to control a safety-critical system with latent dynamics (e.g. for deep brain stimulation) requires taking calculated risks to gain information as efficiently as possible. To address this problem, we present a probabilistically-safe, meta-ac
Externí odkaz:
http://arxiv.org/abs/2007.03742
Autor:
Phalen, Henry, Vagdargi, Prasad, Schrum, Mariah L., Chakravarty, Sumana, Canezin, Amanda, Pozin, Michael, Coemert, Suat, Iordachita, Iulian, Hoffman, Stephen L., Chirikjian, Gregory S., Taylor, Russell H.
The treatment of malaria is a global health challenge that stands to benefit from the widespread introduction of a vaccine for the disease. A method has been developed to create a live organism vaccine using the sporozoites (SPZ) of the parasite Plas
Externí odkaz:
http://arxiv.org/abs/2004.05702
As robots become more prevalent, the importance of the field of human-robot interaction (HRI) grows accordingly. As such, we should endeavor to employ the best statistical practices. Likert scales are commonly used metrics in HRI to measure perceptio
Externí odkaz:
http://arxiv.org/abs/2001.03231
Autor:
Schrum, Mariah, Gombolay, Matthew
Detecting and adapting to catastrophic failures in robotic systems requires a robot to learn its new dynamics quickly and safely to best accomplish its goals. To address this challenging problem, we propose probabilistically-safe, online learning tec
Externí odkaz:
http://arxiv.org/abs/1912.08116
Autor:
Schrum, Mariah, Canezin, Amanda, Chakravarty, Sumana, Laskowski, Michelle, Comert, Suat, Sevimli, Yunuscan, Chirikjian, Gregory S., Hoffman, Stephen L., Taylor, Russell H.
Malaria is the one of the leading causes of morbidity and mortality in many developing countries. The development of a highly effective and readily deployable vaccine represents a major goal for world health. There has been recent progress in develop
Externí odkaz:
http://arxiv.org/abs/1903.02532