PhD student, Tianjin University
2 papers at NeurIPS 2025
An Levenshtein Distance Embedding-based Code for 4-ary IDS Channel
We propose a SNN modeling framework that incorporates synaptic heterogeneity, an essential property largely overlooked in previous studies, and demonstrate its computational advantages and generalizability.
