by Computer Vision Department of NTRLab Suppose we are given a set of distinct points P = {(xi, yi) ∈ ℝm ×ℝ}i=1,...,n which we regard as a set of test samples xi ∈ ℝm with known answers yi ∈ ℝ.
Proceedings of the 1st Annual Conference on Robot Learning on 13-15 November 2017 Published as Volume 78 by the Proceedings of Machine Learning Research on 18 October 2017. Volume Edited by: Sergey Levine Vincent Vanhoucke Ken Goldberg Series Editors: Neil D. Lawrence Mark Reid
Marvin is a deep learning framework designed first and foremost to be hackable. It is naively simple for fast prototyping, uses only basic C/C++, and only calls CUDA and cuDNN as dependencies.
Humans excel at solving a wide variety of challenging problems, from low-level motor control through to high-level cognitive tasks. Our goal at DeepMind is to create artificial agents that can achieve a similar level of performance and generality. Like a human, our agents learn for themselves to achieve successful strategies that lead to the greatest long-term rewards.
A. Boulch, und R. Marlet. Proceedings of the Symposium on Geometry Processing, Seite 281--290. Goslar Germany, Germany, Eurographics Association, (2016)
P. Huang, K. Matzen, J. Kopf, N. Ahuja, und J. Huang. (2018)cite arxiv:1804.00650Comment: CVPR 2018. Project page: https://phuang17.github.io/DeepMVS/ Code: https://github.com/phuang17/DeepMVS.
S. Levine, P. Pastor, A. Krizhevsky, und D. Quillen. (2016)cite arxiv:1603.02199Comment: This is an extended version of "Learning Hand-Eye Coordination for Robotic Grasping with Large-Scale Data Collection," ISER 2016. Draft modified to correct typo in Algorithm 1 and add a link to the publicly available dataset.
H. Lin, M. Tegmark, und D. Rolnick. (2016)cite arxiv:1608.08225Comment: Replaced to match version published in Journal of Statistical Physics: https://link.springer.com/article/10.1007/s10955-017-1836-5 Improved refs & discussion, typos fixed. 16 pages, 3 figs.
A. Mousavian, D. Anguelov, J. Flynn, und J. Kosecka. (2016)cite arxiv:1612.00496Comment: To appear in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017.
V. Patraucean, A. Handa, und R. Cipolla. (2015)cite arxiv:1511.06309Comment: The experiments section has been extended and a direct application to weakly-supervised video segmentation through label propagation has been included.
A. Zeng, S. Song, M. Nießner, M. Fisher, J. Xiao, und T. Funkhouser. (2016)cite arxiv:1603.08182Comment: To appear at the Conference on Computer Vision and Pattern Recognition (CVPR) 2017. Project webpage: http://3dmatch.cs.princeton.edu.
K. Zhang, M. Sun, T. Han, X. Yuan, L. Guo, und T. Liu. (2016)cite arxiv:1608.02908Comment: IEEE Transactions on Circuits and Systems for Video Technology 2017.