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6 papers · 1 filter
Deep Q-learning decoder for depolarizing noise on the toric code
David Fitzek, Mattias Eliasson, Anton Frisk Kockum +1
We present an AI-based decoding agent for quantum error correction of depolarizing noise on the toric code. The agent is trained using deep reinforcement learning (DRL), where an a…
CASAD: CAN-Aware Stealthy-Attack Detection for In-Vehicle Networks
Nasser Nowdehi, Wissam Aoudi, Magnus Almgren +1
Nowadays, vehicles have complex in-vehicle networks (IVNs) with millions of lines of code controlling almost every function in the vehicle including safety-critical functions. It h…
Agility is responsiveness to change: An essential definition
Lucas Gren, Per Lenberg
There is some ambiguity of what agile means in both research and practice. Authors have suggested a diversity of different definitions, through which it is difficult to interpret w…
A System Modeling Approach to Enhance Functional and Software Development
Saurabh Tiwari, Emina Smajlovic, Amina Krekic +1
This paper presents a SysML-based approach to enhance functional and software development process within an industrial context. The recent changes in technology such as electromobi…
Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Driving
Carl-Johan Hoel, Katherine Driggs-Campbell, Krister Wolff +2
Tactical decision making for autonomous driving is challenging due to the diversity of environments, the uncertainty in the sensor information, and the complex interaction with oth…
Towards Structured Evaluation of Deep Neural Network Supervisors
Jens Henriksson, Christian Berger, Markus Borg +4
Deep Neural Networks (DNN) have improved the quality of several non-safety related products in the past years. However, before DNNs should be deployed to safety-critical applicatio…