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27 papers · 1 filter
Fast, Autonomous Flight in GPS-Denied and Cluttered Environments
Kartik Mohta, Michael Watterson, Yash Mulgaonkar +14
One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little…
Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations
Maziar Raissi, Paris Perdikaris, George Em Karniadakis
We introduce physics informed neural networks -- neural networks that are trained to solve supervised learning tasks while respecting any given law of physics described by general…
Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations
Maziar Raissi, Paris Perdikaris, George Em Karniadakis
We introduce physics informed neural networks -- neural networks that are trained to solve supervised learning tasks while respecting any given law of physics described by general…
The Rotation of M Dwarfs Observed by the Apache Point Galactic Evolution Experiment
Steven H. Gilhool, Cullen H. Blake, Ryan C. Terrien +3
We present the results of a spectroscopic analysis of rotational velocities in 714 M dwarf stars observed by the SDSS III Apache Point Galactic Evolution Experiment (APOGEE) survey…
Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap
Aryan Mokhtari, Hamed Hassani, Amin Karbasi
In this paper, we study the problem of \textit{constrained} and \textit{stochastic} continuous submodular maximization. Even though the objective function is not concave (nor conve…
Approximate Supermodularity Bounds for Experimental Design
Luiz F. O. Chamon, Alejandro Ribeiro
This work provides performance guarantees for the greedy solution of experimental design problems. In particular, it focuses on A- and E-optimal designs, for which typical guarante…