Event Related Potentials (ERPs) are modifications of the brain activity in response to external sensory stimulation. P300 is a positive ERP component occurring 300 ms after the presentation of a rare stimulus and indicating the conscious perception of an unexpected change in sensory stimulation....
04b Atto di convegno in volume
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Recent studies, based on Local Field Potentials and source activity reconstruction from electroencephalographic (EEG) signals, conducted in animals and healthy individuals reported a power increase in the frequency range of 3-5 Hz over the cortical motor areas that accompanies the preparatory phase...
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Brain networks represent one of the most fascinating biophysics contributions to modern medicine. Nowadays clinical practice largely benefits from network theory to characterize both physiological and pathological brain networks. However, to date the analysis of such systems still relies on classic...
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Explainable AI seeks to unveil the intricacies of black box models through post-hoc strategies or self-interpretable models. In this paper, we tackle the problem of building layers that are intrinsically explainable through logical rules. In particular, we address current state-of-the-art methods'...
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Non-markovian Reinforcement Learning (RL) tasks are very hard to solve, because agents must consider the entire history of state-action pairs to act rationally in the environment. Most works use symbolic formalisms (as Linear Temporal Logic or automata) to specify the temporally-extended task....
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In this work, we introduce DeepDFA, a novel approach to identifying Deterministic Finite Automata (DFAs) from traces, harnessing a differentiable yet discrete model. Inspired by both the probabilistic relaxation of DFAs and Recurrent Neural Networks (RNNs), our model offers interpretability post-...
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Transfer Learning between non-Markovian RL Tasks through Semantic Representations of Temporal StatesReinforcement Learning (RL) faces challenges in transferring knowledge across tasks efficiently. In this work we focus on transferring policies between different temporally extended tasks expressed in Linear Temporal Logic. Existing methodologies either rely on task-specific representations or...
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Recent advances in protein-protein interaction (PPI) research have harnessed the power of artificial intelligence (AI) to enhance our understanding of protein behaviour. These approaches have become indispensable tools in the field of biology and medicine, enabling scientists to uncover hidden...
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Extended reality offers unprecedented learning and training occasions, and unique challenges related not only to throughput and delay, but also to the characteristic spatial concentration of trainees. We have developed an algorithm for eXtended reality oriented Orchestration of Access Resources (X-...
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Recent studies, based on Local Field Potentials and source activity reconstruction from electroencephalographic (EEG) signals, conducted in animals and healthy individuals reported a power increase in the frequency range of 3-5 Hz over the cortical motor areas that accompanies the preparatory phase...