We perform a benchmarking study to identify the advantages and the drawbacks of Spectral
Clustering and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). We …

In this paper we present a work on encoding, clustering and modeling expert driver
behaviors to be reproduced by an autonomous driving car agent. We collected speed …

This research addresses the growing need for energy efficiency and flexibility in industrial
production processes in the context of the evolving dynamics of the global energy transition …

Unmanned Aerial Vehicle (UAV) imagery is gaining a lot of momentum lately. Indeed,
gathered information from a bird-point-of-view is particularly relevant for numerous …

In this paper we present a method to learn how to drive in different types of blind
intersections using expert driving data. We cluster different intersections based on the …

In order for autonomous vehicles to learn how to naturally navigate through an intersection,
we present a method of learning from expert drivers using inverse reinforcement learning …

Bitcoin is the most popular of a collection of cryptocurriences that have risen to prominence
in recent years, promising a de-centralized approach to currency. A belief in transaction …

In this paper, we present a novel unsupervised domain adaptation framework, Multi-Partition
Feature Alignment Network, that learns a deep neural model for the target domain without …