Bojian Yin

Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks

This paper introduces adaptive spiking recurrent neural networks with a novel surrogate gradient, achieving state-of-the-art performance in time-domain tasks and improved computational efficiency.

Using the structure of genome data in the design of deep neural networks for predicting amyotrophic lateral sclerosis from genotype

This paper develops a deep learning approach to predict ALS from genotype by leveraging genome structure, showing better performance than other methods.