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Pre-stimulus brain activity is thought to modulate visual perception. However, the underlying processes are strongly debated. Moreover, the role of pre-stimulus activity beyond tasks with single, simple stimuli is largely unknown. Here, we analyzed electro ...
Understanding the origins of militarized conflict is a complex, yet important undertaking. Existing research seeks to build this understanding by considering bi-lateral relationships between entity pairs (dyadic causes) and multi-lateral relationships amon ...
Algorithms are now routinely used to make consequential decisions that affect human lives. Examples include college admissions, medical interventions or law enforcement. While algorithms empower us to harness all information hidden in vast amounts of data, ...
Pre-stimulus brain activity is thought to modulate visual perception. However, the nature of this modulation remains debated. In particular, the use of paradigms with very brief and weak stimuli complicates a univocal understanding. Here we focus on phenom ...
Objective. Detection and early prediction of mental fatigue (i.e. shifts in vigilance), could be used to adapt neuromodulation strategies to effectively treat patients suffering from brain injury and other indications with prominent chronic mental fatigue. ...
Face recognition has evolved as a widely used biometric modality. However, its vulnerability against presentation attacks poses a significant security threat. Though presentation attack detection (PAD) methods try to address this issue, they often fail in ...
This paper tackles the problem of adversarial examples from a game theoretic point of view. We study the open question of the existence of mixed Nash equilibria in the zero-sum game formed by the attacker and the classifier. While previous works usually al ...
The World Health Organization (WHO) has stated that effective vector control measures are critical to achieving and sustaining reduction of vector-borne infectious disease incidence. Unmanned aerial vehicles (UAVs), popularly known as drones, can be an imp ...
Training models that perform well under distribution shifts is a central challenge in machine learning. In this paper, we introduce a modeling framework where, in addition to training data, we have partial structural knowledge of the shifted test distribut ...
Face recognition has evolved as a widely used biometric modality. However, its vulnerability against presentation attacks poses a significant security threat. Though presentation attack detection (PAD) methods try to address this issue, they often fail in ...