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Object Shell Reconstruction: Camera-centric Object Representation for Robotic Grasping



Nikhil Chavan-Dafle , Sergiy Popovych , Shubham Agrawal , Daniel D. Lee , Volkan Isler

* 18 pages, 12 figures, 7 tables 

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Curriculum-Driven Multi-Agent Learning and the Role of Implicit Communication in Teamwork



Niko A. Grupen , Daniel D. Lee , Bart Selman

* 18 pages, 10 figures 

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Fairness for Cooperative Multi-Agent Learning with Equivariant Policies



Niko A. Grupen , Bart Selman , Daniel D. Lee

* 15 pages, 4 figures 

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Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization



Travers Rhodes , Daniel D. Lee

* 16 pages, 9 figures 

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Learning Continuous Cost-to-Go Functions for Non-holonomic Systems



Jinwook Huh , Daniel D. Lee , Volkan Isler


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Cost-to-Go Function Generating Networks for High Dimensional Motion Planning



Jinwook Huh , Volkan Isler , Daniel D. Lee


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Low-Bandwidth Communication Emerges Naturally in Multi-Agent Learning Systems



Niko A. Grupen , Daniel D. Lee , Bart Selman

* 10 pages, 6 figures, Appearing in Talking to Strangers: Zero-Shot Emergent Communication Workshop NeurIPS 2020. Fixed part (a) of Figure 2 to include correct baseline reported in quantitative results section 

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Fast Motion Understanding with Spatiotemporal Neural Networks and Dynamic Vision Sensors



Anthony Bisulco , Fernando Cladera Ojeda , Volkan Isler , Daniel D. Lee


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Learning to Generate Cost-to-Go Functions for Efficient Motion Planning



Jinwook Huh , Galen Xing , Ziyun Wang , Volkan Isler , Daniel D. Lee


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