most citedCombining Neural Networks and Tree Search for Task and Motion Planning in Challenging Environments

23 citations · 67 across the 9 of their papers we have counts for

collaborators

13 papers

cs.LG20171 cited

Learning to Imagine Manipulation Goals for Robot Task Planning

Chris Paxton, Kapil Katyal, Christian Rupprecht +2

Prospection is an important part of how humans come up with new task plans, but has not been explored in depth in robotics. Predicting multiple task-level is a challenging problem…

cs.RO2017

Temporal and Physical Reasoning for Perception-Based Robotic Manipulation

Felix Jonathan, Chris Paxton, Gregory D. Hager

Accurate knowledge of object poses is crucial to successful robotic manipulation tasks, and yet most current approaches only work in laboratory settings. Noisy sensors and cluttere…

cs.CV201710 cited

Adversarial Deep Structured Nets for Mass Segmentation from Mammograms

Wentao Zhu, Xiang Xiang, Trac D. Tran +2

Mass segmentation provides effective morphological features which are important for mass diagnosis. In this work, we propose a novel end-to-end network for mammographic mass segmen…

cs.AI201710 cited

Advances in Artificial Intelligence Require Progress Across all of Computer Science

Gregory D. Hager, Randal Bryant, Eric Horvitz +2

Advances in Artificial Intelligence require progress across all of computer science.

cs.CY20174 cited

Research Opportunities and Visions for Smart and Pervasive Health

Elizabeth Mynatt, Gregory D. Hager, Santosh Kumar +4

Improving the health of the nation's population and increasing the capabilities of the US healthcare system to support diagnosis, treatment, and prevention of disease is a critical…

cs.CY2017

A National Research Agenda for Intelligent Infrastructure

Elizabeth Mynatt, Jennifer Clark, Greg Hager +8

Our infrastructure touches the day-to-day life of each of our fellow citizens, and its capabilities, integrity and sustainability are crucial to the overall competitiveness and pro…