most citedImproving Cancer Imaging Diagnosis with Bayesian Networks and Deep Learning: A Bayesian Deep Learning Approach

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2024★ 1 cited

Improving Cancer Imaging Diagnosis with Bayesian Networks and Deep Learning: A Bayesian Deep Learning Approach

Pei Xi, Lin

With recent advancements in the development of artificial intelligence applications using theories and algorithms in machine learning, many accurate models can be created to train…

cs.LG2023

NetDistiller: Empowering Tiny Deep Learning via In-Situ Distillation

Shunyao Zhang, Yonggan Fu, Shang Wu +4

Boosting the task accuracy of tiny neural networks (TNNs) has become a fundamental challenge for enabling the deployments of TNNs on edge devices which are constrained by strict li…