6 accepted papers
Affective multimedia content has long been used as stimulation to study an individual's personality using physiology. In this work, we propose a novel Siamese Content-Attentive Graph Convolutional Network (SCA-GCN) to learn a discriminative physiology representation jointly guided by the actual vide…
There is a growing number of large scale cross-site database collection of resting-state functional magnetic resonance imaging (rs-fMRI) for studying neurobehavioral diseases, such as ADHD. Although a large amount of data benefits machine learning-based classification methods, the idiosyncratic vari…
Studies have shown that people with different personalities would result in a different physiological reaction when encountering emotional stimulus. In this work, we propose an attribute-invariance loss embedded variational autoencoder (AI-VAE) to learn the personality-invariant physiological signal…
Human adapt their behaviors by continuously monitoring one another to function socially in our society. The ability to process face identity from memory is a crucial basic capability. In this work, we propose an event-contrastive connectome network (E-cCN) in representing brain's functional connecti…
Studies have shown that measures of personal physiology, e.g., blood pressure (BP) variation and heart rate variability (HRV), is closely related to a subject's psychological states and are being used regularly to track patients' health conditions in medical settings. The conventional method of moni…
Understanding neuro-perceptual mechanism of vocal emotion perception continues to be an important research direction not only in advancing scientific knowledge but also in inspiring more robust affective computing technologies. The large variabilities in the manifested fMRI signals among subjects ha…