Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Bhairav Mehta"'
Autor:
Emilio Frazzoli, Gianmarco Bernasconi, Amaury Camus, Bhairav Mehta, Matthew R. Walter, Liam Paull, Andrea Censi, Jacopo Tani, Rohit Suri, Andrea F. Daniele, Aleksandar Petrov, Anthony Courchesne, Tomasz Zaluska
Publikováno v:
IROS
As robotics matures and increases in complexity, it is more necessary than ever that robot autonomy research be reproducible. Compared to other sciences, there are specific challenges to benchmarking autonomy, such as the complexity of the software s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73846c72375d5314861335d6a1dafac8
http://arxiv.org/abs/2009.04362
http://arxiv.org/abs/2009.04362
Autor:
A. Kirsten Bowser, Jacopo Tani, Matthew R. Walter, Breandan Considine, Andrea Censi, Ruslan Hristov, Gianmarco Bernasconi, Andrea F. Daniele, Julian Zilly, Liam Paull, Emilio Frazzoli, Claudio Ruch, Florian Golemo, Bhairav Mehta, Manfred Diaz, Jan Hakenberg, Sunil Mallya
Publikováno v:
The Springer Series on Challenges in Machine Learning
The NeurIPS '18 Competition. From Machine Learning to Intelligent Conversations
The NeurIPS '18 Competition ISBN: 9783030291341
The NeurIPS '18 Competition. From Machine Learning to Intelligent Conversations
The NeurIPS '18 Competition ISBN: 9783030291341
Despite recent breakthroughs, the ability of deep learning and reinforcement learning to outperform traditional approaches to control physically embodied robotic agents remains largely unproven. To help bridge this gap, we present the “AI Driving O
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41fc569059db2d78589eea957d5cff7b
http://arxiv.org/abs/1903.02503
http://arxiv.org/abs/1903.02503
Autor:
Michael, Salerno, Rajesh, Janardhanan, Ronny S, Jiji, Jeremy, Brooks, Nebiyu, Adenaw, Bhairav, Mehta, Yang, Yang, Patrick, Antkowiak, Christopher M, Kramer, Frederick H, Epstein
Publikováno v:
Journal of magnetic resonance imaging : JMRI. 38(1)
To develop and validate modified Look-Locker (MOLLI) protocols to generate myocardial T1 maps within clinically acceptable breath-hold durations and to compare partition coefficients (λ) of gadolinium (Gd)-DTPA determined from either bolus injection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::2fc02697dfe881a2b2b9efe622135ebd
https://pubmed.ncbi.nlm.nih.gov/23197434
https://pubmed.ncbi.nlm.nih.gov/23197434
