Justin S. Smith | DeepAI

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Featured Co-authors

Jie Chen
218 publications
Patricio A. Vela
34 publications
Nicholas Lubbers
10 publications
Yipu Zhao
10 publications
Haoxin Ma
9 publications
Fu-Jen Chu
8 publications
Kipton Barros
5 publications
Aidan P. Thompson
4 publications
Olexandr Isayev
4 publications
Shiyu Feng
4 publications
Alexander H. Chang
3 publications

∙ 03/02/2021

NavTuner: Learning a Scene-Sensitive Family of Navigation Policies

The advent of deep learning has inspired research into end-to-end learni...

0 Haoxin Ma, et al. ∙

∙ 08/23/2020

Good Graph to Optimize: Cost-Effective, Budget-Aware Bundle Adjustment in Visual SLAM

The cost-efficiency of visual(-inertial) SLAM (VSLAM) is a critical char...

0 Yipu Zhao, et al. ∙

∙ 06/09/2020

Simple and efficient algorithms for training machine learning potentials to force data

Abstract Machine learning models, trained on data from ab initio quantum...

0 Justin S. Smith, et al. ∙

∙ 03/10/2020

Automated discovery of a robust interatomic potential for aluminum

Atomistic molecular dynamics simulation is an important tool for predict...

0 Justin S. Smith, et al. ∙

∙ 03/03/2020

Closed-Loop Benchmarking of Stereo Visual-Inertial SLAM Systems: Understanding the Impact of Drift and Latency on Tracking Accuracy

Visual-inertial SLAM is essential for robot navigation in GPS-denied env...

0 Yipu Zhao, et al. ∙

∙ 08/19/2019

Autonomous, Monocular, Vision-Based Snake Robot Navigation and Traversal of Cluttered Environments using Rectilinear Gait Motion

Rectilinear forms of snake-like robotic locomotion are anticipated to be...

6 Alexander H. Chang, et al. ∙

∙ 01/28/2018

Less is more: sampling chemical space with active learning

The development of accurate and transferable machine learning (ML) poten...

0 Justin S. Smith, et al. ∙

∙ 01/16/2018

Learning to Navigate: Exploiting Deep Networks to Inform Sample-Based Planning During Vision-Based Navigation

Recent applications of deep learning to navigation have generated end-to...

0 Justin S. Smith, et al. ∙

∙ 09/29/2017

Hierarchical modeling of molecular energies using a deep neural network

We introduce the Hierarchically Interacting Particle Neural Network (HIP...

0 Nicholas Lubbers, et al. ∙

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