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A Counterfactual Safety Margin Perspective on the Scoring of Autonomous Vehicles' Riskiness
(2023)arXivAutonomous Vehicles (AVs) promise a range of societal advantages, including broader access to mobility, reduced road accidents, and enhanced transportation efficiency. However, evaluating the risks linked to AVs is complex due to limited historical data and the swift progression of technology. This paper presents a data-driven framework for assessing the risk of different AVs' behaviors in various operational design domains (ODDs), based ...Working Paper -
Efficient Biologically Plausible Adversarial Training
(2023)arXivArtificial Neural Networks (ANNs) trained with Backpropagation (BP) show astounding performance and are increasingly often used in performing our daily life tasks. However, ANNs are highly vulnerable to adversarial attacks, which alter inputs with small targeted perturbations that drastically disrupt the models' performance. The most effective method to make ANNs robust against these attacks is adversarial training, in which the training ...Working Paper -
NanoSLAM: Enabling Fully Onboard SLAM for Tiny Robots
(2023)arXivPerceiving and mapping the surroundings are essential for enabling autonomous navigation in any robotic platform. The algorithm class that enables accurate mapping while correcting the odometry errors present in most robotics systems is Simultaneous Localization and Mapping (SLAM). Today, fully onboard mapping is only achievable on robotic platforms that can host high-wattage processors, mainly due to the significant computational load ...Working Paper -
Fully Onboard SLAM for Distributed Mapping with a Swarm of Nano-Drones
(2023)arXivThe use of Unmanned Aerial Vehicles (UAVs) is rapidly increasing in applications ranging from surveillance and first-aid missions to industrial automation involving cooperation with other machines or humans. To maximize area coverage and reduce mission latency, swarms of collaborating drones have become a significant research direction. However, this approach requires open challenges in positioning, mapping, and communications to be ...Working Paper -
Non steady-state thermometry with optical diffraction tomography
(2023)arXivMeasurement of local temperature using label-free optical methods has gained importance as a pivotal tool in both fundamental and applied research. Yet, most of these approaches are limited to steady-state measurements of planar heat sources. However, the time taken to reach steady-state is a complex function of the volume of the heated system, the size of the heat source, and the thermal conductivity of the surroundings. As such, said ...Working Paper -
Robust Feature Selection for Continuous BP Estimation in Multiple Populations: Towards Cuffless Ambulatory BP Monitoring
(2023)TechRxivCurrent blood pressure (BP) estimation methods have not achieved an accurate and adaptable approach for application in populations at risk of cardiovascular disease, with generally limited sample sizes. Here, we introduce an algorithm for BP estimation solely reliant on photoplethysmography (PPG) signals and demographic features. Our approach automatically obtains signal features and employs the Markov Blanket (MB) feature selection to ...Working Paper -
Delaying Decisions and Reservation Costs
(2023)arXivWe study the Feedback Vertex Set and the Vertex Cover problem in a natural variant of the classical online model that allows for delayed decisions and reservations. Both problems can be characterized by an obstruction set of subgraphs that the online graph needs to avoid. In the case of the Vertex Cover problem, the obstruction set consists of an edge (i.e., the graph of two adjacent vertices), while for the Feedback Vertex Set problem, ...Working Paper -
Interpretable and Intervenable Ultrasonography-based Machine Learning Models for Pediatric Appendicitis
(2023)arXivAppendicitis is among the most frequent reasons for pediatric abdominal surgeries. With recent advances in machine learning, data-driven decision support could help clinicians diagnose and manage patients while reducing the number of non-critical surgeries. Previous decision support systems for appendicitis focused on clinical, laboratory, scoring and computed tomography data, mainly ignoring abdominal ultrasound, a noninvasive and readily ...Working Paper -
PAC-Bayesian Meta-Learning: From Theory to Practice
(2022)arXivMeta-Learning aims to accelerate the learning on new tasks by acquiring useful inductive biases from related data sources. In practice, the number of tasks available for meta-learning is often small. Yet, most of the existing approaches rely on an abundance of meta-training tasks, making them prone to overfitting. How to regularize the meta-learner to ensure generalization to unseen tasks, is a central question in the literature. We provide ...Working Paper -
Environmental Change and Migration Aspirations: Evidence from Bangladesh
(2022)SocArXivThe argument that environmental change is an important driving force of migration has experienced a strong revival in the climate change context. We examine whether and how different environmental stressors aspire people to move. The analysis relies on newly collected, cross-sectional survey data of 1594 households residing in 36 villages along the 250 kilometers of the Jamuna River in Bangladesh – an area affected primarily by floods and ...Working Paper