Fetching the paper…
Reading the bibliography…
Several recent studies have demonstrated the promise of deep visuomotor policies for robot manipulator control.
C. M. Bishop, “Mixture density networks,” Aston University, Tech. Rep., 1994
1994
Earlier work this paper cites.
S. Lawrence, C. L. Giles, and A. C. Tsoi, “Lessons in neural network training: Overfitting may be harder than expected,” in
1997
Earlier work this paper cites.
C. Buciluǎ, R. Caruana, and A. Niculescu-Mizil, “Model compression,” in
2006
Earlier work this paper cites.
C. Chabris and D. Simons,
2010
Earlier work this paper cites.
S. Tellex, T. Kollar, S. Dickerson, M. R. Walter, A. G. Banerjee, S. Teller, and N. Roy, “Understanding natural language commands for robotic navigation and mobile manipulation,” in
2011
Earlier work this paper cites.
A. Graves, “Generating sequences with recurrent neural networks,”
2013
Earlier work this paper cites.
K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition,”
2014
Earlier work this paper cites.
2015
Earlier work this paper cites.
M. Watter, J. Springenberg, J. Boedecker, and M. Riedmiller, “Embed to control: A locally linear latent dynamics model for control from raw images,” in
2015
Earlier work this paper cites.
G. Hinton, O. Vinyals, and J. Dean, “Distilling the knowledge in a neural network,”
2015
Earlier work this paper cites.
2015
Cited alongside, same era.
S. Levine, C. Finn, T. Darrell, and P. Abbeel, “End-to-end training of deep visuomotor policies,”
2016
Cited alongside, same era.
D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. Van Den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot,
2016
Cited alongside, same era.
Q. You, H. Jin, Z. Wang, C. Fang, and J. Luo, “Image captioning with semantic attention,” in
2016
Cited alongside, same era.
Z. Yang, X. He, J. Gao, L. Deng, and A. Smola, “Stacked attention networks for image question answering,” in
2016
Cited alongside, same era.
C. Finn and S. Levine, “Deep visual foresight for planning robot motion,” in
2017
Later among the works it cites.
A. Mazaheri, D. Zhang, and M. Shah, “Video fill in the blank using LR/RL LSTMs with spatial-temporal attentions,” in
2017
Later among the works it cites.
D. Yu, J. Fu, T. Mei, and Y. Rui, “Multi-level attention networks for visual question answering,” in
2017
Later among the works it cites.
2017
Later among the works it cites.
S. Levine, P. Pastor, A. Krizhevsky, J. Ibarz, and D. Quillen, “Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection,”
2018
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen, “Improved techniques for training GANs,” in
2016
Cited alongside, same era.
D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton,
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Y. Duan, M. Andrychowicz, B. Stadie, O. J. Ho, J. Schneider, I. Sutskever, P. Abbeel, and W. Zaremba, “One-shot imitation learning,” in
2017
Cited alongside, same era.
2017
Cited alongside, same era.
R. Rahmatizadeh, P. Abolghasemi, L. Bölöni, and S. Levine, “Vision-based multi-task manipulation for inexpensive robots using end-to-end learning from demonstration,” in
2018
Closest in time.
2018
Closest in time.
L. Yu, Z. Lin, X. Shen, J. Yang, X. Lu, M. Bansal, and T. L. Berg, “MAttNet: Modular attention network for referring expression comprehension,” in
2018
Closest in time.
K. Xu, J. Ba, R. Kiros, K. Cho, A. Courville, R. Salakhudinov, R. Zemel, and Y. Bengio, “Show, attend and tell: Neural image caption generation with visual attention,” in
2057
Closest in time.