activity
20122022
most citedLIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

101 citations · 276 across the 27 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

cs.RO20191 cited

Online Multi-Target Tracking for Maneuvering Vehicles in Dynamic Road Context

Zehui Meng, Qi Heng Ho, Zefan Huang +3

Target detection and tracking provides crucial information for motion planning and decision making in autonomous driving. This paper proposes an online multi-object tracking (MOT)…

cs.RO2019

Deep Context Maps: Agent Trajectory Prediction using Location-specific Latent Maps

Igor Gilitschenski, Guy Rosman, Arjun Gupta +2

In this paper, we propose a novel approach for agent motion prediction in cluttered environments. One of the main challenges in predicting agent motion is accounting for location a…

cs.LG2019

Provable Filter Pruning for Efficient Neural Networks

Lucas Liebenwein, Cenk Baykal, Harry Lang +2

We present a provable, sampling-based approach for generating compact Convolutional Neural Networks (CNNs) by identifying and removing redundant filters from an over-parameterized…

cs.LG2019

SiPPing Neural Networks: Sensitivity-informed Provable Pruning of Neural Networks

Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski +2

We introduce a pruning algorithm that provably sparsifies the parameters of a trained model in a way that approximately preserves the model's predictive accuracy. Our algorithm use…

cs.LG2019

Deep Evidential Regression

Alexander Amini, Wilko Schwarting, Ava Soleimany +1

Deterministic neural networks (NNs) are increasingly being deployed in safety critical domains, where calibrated, robust, and efficient measures of uncertainty are crucial. In this…