Özdenizci et al. propose an adversarial inference approach to extend deep learning models to learn session-invariant person-discriminative representations.
Nezamfar et al. compare the efficacy of a BCI input signal, code-VEP via Electroencephalography, against eye gaze tracking.
Koçanaoğulları et al. propose an active querying procedure using mutual information maximization in recursive state estimation
Koçanaoğulları et al. introduce a novel sequential adaptive action value function for query selection using the multi-armed bandit framework.
Klein et al. present a case of an individual with presumed locked-in syndrome enrolled in an exploratory BCI study.
Kadioglu et al. (2018) present a solution for robust PCA (RPCA) of fully observed data with outlying samples based on M-estimation theory.
Ahani et al. assess the ERP shape, classification accuracy, and typing performance of different BCI presentation paradigms on 10 healthy participants.
Gonzalez-Navarro et al. used data from 10 healthy participants to fit and compare two models: the proposed sequence-based EEG model and the trial-based feature-class-conditional distribution model.
McNaughton et al. describe strategies to build capacity and awareness in the AAC field to ensure appropriate AAC supports are provided.
Light et al. review the state of the science related to AAC technologies that are developmentally appropriate and responsive to the needs of children with CCN and their partners.