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When Your AI Becomes a Target: AI Security Incidents and Best Practices

In contrast to vast academic efforts to study AI security, few real-world reports of AI security incidents exist. Released incidents prevent a thorough investigation of the attackers' motives, as crucial information about the company and AI application is ...

AAAI Press2024

Re-evaluating the mythical divide between traditional and novel cardiovascular risk factors in rheumatoid arthritis

Mats Julius Stensrud

Cardiovascular (CV) risk factors for rheumatoid arthritis (RA) are conventionally classified as 'traditional' and 'novel'. We argue that this classification is obsolete and potentially counterproductive. Further, we discuss problems with the common practic ...

Bmj Publishing Group2024

Impact of microwave beam scattering by density fluctuations on the electron-cyclotron power deposition profile in tokamaks

Stefano Coda, Joan Decker, Oleg Krutkin, Umesh Kumar, Jean Arthur Cazabonne

Electron-cyclotron waves are a tool commonly used in tokamaks, in particular to drive current. Their ability to drive current in a very localized manner renders them an optimal tool for MHD mode mitigation. However, such applications require high accuracy ...

IOP Publishing Ltd2024

Diffusion in Style

Sabine Süsstrunk, Radhakrishna Achanta, Mahmut Sami Arpa, Martin Nicolas Everaert

We present Diffusion in Style, a simple method to adapt Stable Diffusion to any desired style, using only a small set of target images. It is based on the key observation that the style of the images generated by Stable Diffusion is tied to the initial lat ...

2023

Data-Driven Behaviour Estimation in Parametric Games

Anna Maria Maddux, Nicolò Pagan

A central question in multi-agent strategic games deals with learning the underlying utilities driving the agents' behaviour. Motivated by the increasing availability of large data-sets, we develop an unifying data-driven technique to estimate agents' util ...

Elsevier2023

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

Jean-Philippe Thiran, Roser Vinals Terres

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

2023

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Jiancheng Yang, Li Zhang, Zhigang Li, Bo Du

Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesi ...

Springer International Publishing Ag2023

Segmenting Without Annotating: Crack Segmentation and Monitoring via Post-Hoc Classifier Explanations

Devis Tuia, Olga Fink, Florent Evariste Forest, Hugo Laurent Pascal Porta

Monitoring the cracks in walls, roads and other types of infrastructure is essential to ensure the safety of a structure, and plays an important role in structural health monitoring. Automatic visual inspection allows an efficient, costeffective and safe h ...

Research Publishing2023

Model-based impurity emission front control using deuterium fueling and nitrogen seeding in TCV

Basil Duval, Christian Gabriel Theiler, Cristian Galperti, Artur Perek

This paper presents the first result using nitrogen-seeded exhaust feedback control of the NII impurity emission front in TCV. The NII emission front position is consistently located below its commonly used CIII counterpart, indicating the NII emission fro ...

IOP Publishing Ltd2023

DatAFLow: Toward a Data-flow-guided Fuzzer

Mathias Josef Payer

This Replicating Computational Report (RCR) describes (a) our datAFLow fuzzer and (b) how to replicate the results in "datAFLow: Toward a Data-Flow-Guided Fuzzer." Our primary artifact is the datAFLow fuzzer. Unlike traditional coverage-guided greybox fuzz ...

2023