Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning

17 May 2024

Papers citing "Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning"

7 / 7 papers shown

Title
VAE-based Feature Disentanglement for Data Augmentation and Compression in Generalized GNSS Interference Classification Lucas Heublein Simon Kocher Tobias Feigl A. Rügamer Christopher Mutschler Felix Ott DRL 26 1 0 14 Apr 2025
Evaluation of (Un-)Supervised Machine Learning Methods for GNSS Interference Classification with Real-World Data Discrepancies Lucas Heublein N. Raichur Tobias Feigl Tobias Brieger Fin Heuer Lennart Asbach A. Rügamer Felix Ott 47 7 0 31 Mar 2025
Federated Learning with MMD-based Early Stopping for Adaptive GNSS Interference Classification Nishant S. Gaikwad Lucas Heublein N. Raichur Tobias Feigl Christopher Mutschler Felix Ott 45 5 0 31 Dec 2024
Achieving Generalization in Orchestrating GNSS Interference Monitoring Stations Through Pseudo-Labeling Lucas Heublein Tobias Feigl A. Rügamer Felix Ott 38 3 0 03 Oct 2024
Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization Lucas Heublein Tobias Feigl Thorsten Nowak A. Rügamer Christopher Mutschler Felix Ott 29 6 0 23 Sep 2024
Class-Balancing Diffusion Models Yiming Qin Huangjie Zheng Jiangchao Yao Mingyuan Zhou Ya-Qin Zhang DiffM 22 41 0 30 Apr 2023
Class-Incremental Exemplar Compression for Class-Incremental Learning Zilin Luo Yaoyao Liu Bernt Schiele Qianru Sun VLM CLL 73 44 0 24 Mar 2023