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Found 5 papers, 0 papers with code
Fixating on Attention: Integrating Human Eye Tracking into Vision Transformers
We find that the ViT performance is improved in accuracy and number of training epochs when using JSF and FAX.
Bayesian Beta-Bernoulli Process Sparse Coding with Deep Neural Networks
Several approximate inference methods have been proposed for deep discrete latent variable models.
Improving Prediction of Cognitive Performance using Deep Neural Networks in Sparse Data
Cognition in midlife is an important predictor of age-related mental decline and statistical models that predict cognitive performance can be useful for predicting decline.
Bayesian recurrent state space model for rs-fMRI
We evaluate our method on the ADNI2 dataset by inferring latent state patterns corresponding to altered neural circuits in individuals with Mild Cognitive Impairment (MCI).
Deep Bayesian Nonparametric Factor Analysis
We propose a deep generative factor analysis model with beta process prior that can approximate complex non-factorial distributions over the latent codes.
