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PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging
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PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging

Anthony Sicilia
Xingchen Zhao
Anastasia Sosnovskikh
Seong Jae Hwang
ArXiv (abs)PDFHTML

Papers citing "PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging"

3 / 3 papers shown
Title
FedHPL: Efficient Heterogeneous Federated Learning with Prompt Tuning and Logit Distillation
FedHPL: Efficient Heterogeneous Federated Learning with Prompt Tuning and Logit Distillation
Yuting Ma
Lechao Cheng
Yaxiong Wang
Zhun Zhong
Xiaohua Xu
Meng Wang
FedML
82
4
0
27 May 2024
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Haitao Mao
Zhikai Chen
Wei Jin
Haoyu Han
Yao Ma
Tong Zhao
Neil Shah
Jiliang Tang
116
36
0
02 Jun 2023
Modeling Non-Cooperative Dialogue: Theoretical and Empirical Insights
Modeling Non-Cooperative Dialogue: Theoretical and Empirical Insights
Anthony Sicilia
Tristan D. Maidment
Pat Healy
Malihe Alikhani
44
3
0
15 Jul 2022

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