Jeremy L Wyatt
Jeremy L Wyatt
Director, Applied Science, Amazon
Bestätigte E-Mail-Adresse bei
Zitiert von
Zitiert von
Diversity creation methods: a survey and categorisation
G Brown, J Wyatt, R Harris, X Yao
Information fusion 6 (1), 5-20, 2005
Managing diversity in regression ensembles.
G Brown, JL Wyatt, P Tino
Journal of machine learning research 6 (9), 2005
The strands project: Long-term autonomy in everyday environments
N Hawes, C Burbridge, F Jovan, L Kunze, B Lacerda, L Mudrova, J Young, ...
IEEE Robotics & Automation Magazine 24 (3), 146-156, 2017
Robot task planning and explanation in open and uncertain worlds
M Hanheide, M Göbelbecker, GS Horn, A Pronobis, K Sjöö, A Aydemir, ...
Artificial Intelligence 247, 119-150, 2017
One-shot learning and generation of dexterous grasps for novel objects
M Kopicki, R Detry, M Adjigble, R Stolkin, A Leonardis, JL Wyatt
The International Journal of Robotics Research 35 (8), 959-976, 2016
Functional object class detection based on learned affordance cues
M Stark, P Lies, M Zillich, J Wyatt, B Schiele
Computer Vision Systems: 6th International Conference, ICVS 2008 Santorini …, 2008
Exploration and inference in learning from reinforcement
J Wyatt
University of Edinburgh. College of Science and Engineering. School of …, 1998
Slurs, roles and power
M Popa-Wyatt, JL Wyatt
Philosophical Studies, 2017
REBA: A Refinement-Based Architecture for Knowledge Representation and Reasoning in Robotics
M Sridharan, M Gelfond, S Zhang, J Wyatt
Journal of Artificial Intelligence Research 65, 2019
Modeling of deformable objects for robotic manipulation: A tutorial and review
VE Arriola-Rios, P Guler, F Ficuciello, D Kragic, B Siciliano, JL Wyatt
Frontiers in Robotics and AI 7, 82, 2020
Towards an integrated robot with multiple cognitive functions
N Hawes, A Sloman, J Wyatt, M Zillich, H Jacobsson, GJM Kruijff, ...
AAAI 7, 1548-1553, 2007
Learning to predict how rigid objects behave under simple manipulation
M Kopicki, S Zurek, R Stolkin, T Mörwald, J Wyatt
2011 IEEE international conference on robotics and automation, 5722-5729, 2011
Exploiting probabilistic knowledge under uncertain sensing for efficient robot behaviour
M Hanheide, C Gretton, R Dearden, N Hawes, J Wyatt, A Pronobis, ...
IJCAI Proceedings-International Joint Conference on Artificial Intelligence …, 2011
Planning to see: A hierarchical approach to planning visual actions on a robot using POMDPs
M Sridharan, J Wyatt, R Dearden
Artificial Intelligence 174 (11), 704-725, 2010
Mixed Logical Inference and Probabilistic Planning for Robots in Unreliable Worlds
S Zhang, M Sridharan, JL Wyatt
IEEE Transactions on Robotics 31 (3), 699 - 713, 2015
Mediating between qualitative and quantitative representations for task-orientated human-robot interaction.
M Brenner, JD Kelleher, N Hawes, J Wyatt
Technological University Dublin, 2007
Two-level RRT planning for robotic push manipulation
C Zito, R Stolkin, M Kopicki, JL Wyatt
Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International …, 2012
Correlation-based intrinsic image extraction from a single image
X Jiang, AJ Schofield, JL Wyatt
Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010
Crossmodal content binding in information-processing architectures
H Jacobsson, N Hawes, GJ Kruijff, J Wyatt
Proceedings of the 3rd ACM/IEEE international conference on Human robot …, 2008
Cognitive systems
HI Christensen, GJ Kruijff, JL Wyatt
Springer Verlag, 2010
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