Zobrazeno 1 - 10
of 260
pro vyhledávání: '"Sullivan, Michael B."'
Autor:
Hsiao, Yu-Shun, Hari, Siva Kumar Sastry, Filipiuk, Michał, Tsai, Timothy, Sullivan, Michael B., Reddi, Vijay Janapa, Singh, Vasu, Keckler, Stephen W.
The processing requirement of autonomous vehicles (AVs) for high-accuracy perception in complex scenarios can exceed the resources offered by the in-vehicle computer, degrading safety and comfort. This paper proposes a sensor frame processing rate (F
Externí odkaz:
http://arxiv.org/abs/2205.03347
Autor:
Trinh, Quang Thang, Le Van, Tuyen, Phan, Thi To Nga, Ong, Khuong Phuong, Kosslick, Hendrik, Amaniampong, Prince Nana, Sullivan, Michael B., Chu, Hong-Son, An, Hongjie, Nguyen, Tuan-Khoa, Zhang, Jun, Zhang, Jia, Huyen, Pham Thanh, Nguyen, Nam-Trung
Publikováno v:
In Journal of Alloys and Compounds 15 October 2024 1002
Autor:
Arce-Ramos, Juan Manuel, Li, Wen-Qing, Lim, San Hua, Chang, Jie, Hashimoto, Takuya, Kamata, Hiroyuki, Sullivan, Michael B., Borgna, Armando, Chen, Luwei, Poh, Chee Kok, Zhang, Jia
Publikováno v:
In Applied Catalysis B: Environment and Energy 15 June 2024 347
Autor:
Deng, Tianqi, Recatala-Gomez, Jose, Ohnishi, Masato, Repaka, D. V. Maheshwar, Kumar, Pawan, Suwardi, Ady, Abutaha, Anas, Nandhakumar, Iris, Biswas, Kanishka, Sullivan, Michael B., Wu, Gang, Shiomi, Junichiro, Yang, Shuo-Wang, Hippalgaonkar, Kedar
The discovery of novel materials for thermoelectric energy conversion has potential to be accelerated by data-driven screening combined with high-throughput calculations. One way to increase the efficacy of successfully choosing a candidate material
Externí odkaz:
http://arxiv.org/abs/2101.03340
The ability of Convolutional Neural Networks (CNNs) to accurately process real-time telemetry has boosted their use in safety-critical and high-performance computing systems. As such systems require high levels of resilience to errors, CNNs must exec
Externí odkaz:
http://arxiv.org/abs/2006.04984
Autor:
Mahmoud, Abdulrahman, Hari, Siva Kumar Sastry, Fletcher, Christopher W., Adve, Sarita V., Sakr, Charbel, Shanbhag, Naresh, Molchanov, Pavlo, Sullivan, Michael B., Tsai, Timothy, Keckler, Stephen W.
As Convolutional Neural Networks (CNNs) are increasingly being employed in safety-critical applications, it is important that they behave reliably in the face of hardware errors. Transient hardware errors may percolate undesirable state during execut
Externí odkaz:
http://arxiv.org/abs/2002.09786
Autor:
Li, Chenfei, Kong, Xin Ying, Lyu, Maoping, Tay, Xiu Ting, Đokić, Miloš, Chin, Kek Foo, Yang, Crystal Ting, Lee, Erin Ke Xin, Zhang, Jinfan, Tham, Chun Yuan, Chan, Wei Xin, Lee, Wen Jie, Lim, Teik Thye, Goto, Atsushi, Sullivan, Michael B., Soo, Han Sen
Publikováno v:
In Chem 14 September 2023 9(9):2683-2700
Autor:
Jha, Saurabh, Banerjee, Subho S., Tsai, Timothy, Hari, Siva K. S., Sullivan, Michael B., Kalbarczyk, Zbigniew T., Keckler, Stephen W., Iyer, Ravishankar K.
The safety and resilience of fully autonomous vehicles (AVs) are of significant concern, as exemplified by several headline-making accidents. While AV development today involves verification, validation, and testing, end-to-end assessment of AV syste
Externí odkaz:
http://arxiv.org/abs/1907.01051
Autor:
Li, Wen-Qing, Manuel Arce-Ramos, Juan, Sullivan, Michael B., Kok Poh, Chee, Chen, Luwei, Borgna, Armando, Zhang, Jia
Publikováno v:
In Journal of Catalysis March 2023
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