7 citations · 9 across the 3 of their papers we have counts for
4 papers
Mars Terrain Segmentation with Less Labels
Edwin Goh, Jingdao Chen, Brian Wilson
Planetary rover systems need to perform terrain segmentation to identify drivable areas as well as identify specific types of soil for sample collection. The latest Martian terrain…
-MILP: Deep Space Network Scheduling via Mixed-Integer Linear Programming
Thomas Claudet, Ryan Alimo, Edwin Goh +3
This paper introduces -MILP, a powerful variant of the mixed-integer linear programming (MILP) optimization framework to solve NASA's Deep Space Network (DSN) scheduling problem…
Scheduling the NASA Deep Space Network with Deep Reinforcement Learning
Edwin Goh, Hamsa Shwetha Venkataram, Mark Hoffmann +2
With three complexes spread evenly across the Earth, NASA's Deep Space Network (DSN) is the primary means of communications as well as a significant scientific instrument for dozen…
MARVIN: An Open Machine Learning Corpus and Environment for Automated Machine Learning Primitive Annotation and Execution
Chris A. Mattmann, Sujen Shah, Brian Wilson
In this demo paper, we introduce the DARPA D3M program for automatic machine learning (ML) and JPL's MARVIN tool that provides an environment to locate, annotate, and execute machi…