There is a growing interest in characterizing circular data found in
bio...
Modern transformer-based models designed for computer vision have
outper...
Several approximate inference methods have been proposed for deep discre...
Cognition in midlife is an important predictor of age-related mental dec...
We propose a hierarchical Bayesian recurrent state space model for model...
We propose a deep generative factor analysis model with beta process pri...
Simultaneous EEG-fMRI is a multi-modal neuroimaging technique that provi...
Many imaging technologies rely on tomographic reconstruction, which requ...
In reinforcement learning (RL), sparse rewards are a natural way to spec...
Steady-State Visual Evoked Potentials (SSVEPs) are neural oscillations f...
Reinforcement Learning AI commonly uses reward/penalty signals that are
...
Multimodal biosignal acquisition is facilitated by recently introduced
s...
Simultaneously recorded electroencephalography (EEG) and functional magn...
We present an efficient algorithm for simultaneously training sparse
gen...