Guardado en:
| Autores principales: | Babendererde, Niklas, Zhu, Haozhe, Fuchs, Moritz, Stieber, Jonathan, Mukhopadhyay, Anirban |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2501.04588 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
FrOoDo: Framework for Out-of-Distribution Detection
por: Stieber, Jonathan, et al.
Publicado: (2022)
por: Stieber, Jonathan, et al.
Publicado: (2022)
GAUDA: Generative Adaptive Uncertainty-guided Diffusion-based Augmentation for Surgical Segmentation
por: Frisch, Yannik, et al.
Publicado: (2025)
por: Frisch, Yannik, et al.
Publicado: (2025)
ASMR: Angular Support for Malfunctioning Client Resilience in Federated Learning
por: Konstantin, Mirko, et al.
Publicado: (2025)
por: Konstantin, Mirko, et al.
Publicado: (2025)
Federated Continual Instruction Tuning
por: Guo, Haiyang, et al.
Publicado: (2025)
por: Guo, Haiyang, et al.
Publicado: (2025)
FDRMFL:Multi-modal Federated Feature Extraction Model Based on Information Maximization and Contrastive Learning
por: Wu, Haozhe
Publicado: (2025)
por: Wu, Haozhe
Publicado: (2025)
OctreeNCA: Single-Pass 184 MP Segmentation on Consumer Hardware
por: Lemke, Nick, et al.
Publicado: (2025)
por: Lemke, Nick, et al.
Publicado: (2025)
Knowledge-guided Continual Learning for Behavioral Analytics Systems
por: Senarath, Yasas, et al.
Publicado: (2025)
por: Senarath, Yasas, et al.
Publicado: (2025)
Federated Continual Graph Learning
por: Zhu, Yinlin, et al.
Publicado: (2024)
por: Zhu, Yinlin, et al.
Publicado: (2024)
Bayesian Federated Learning for Continual Training
por: Milasheuski, Usevalad, et al.
Publicado: (2025)
por: Milasheuski, Usevalad, et al.
Publicado: (2025)
Federated Continual Learning: Concepts, Challenges, and Solutions
por: Hamedi, Parisa, et al.
Publicado: (2025)
por: Hamedi, Parisa, et al.
Publicado: (2025)
Accurate Forgetting for Heterogeneous Federated Continual Learning
por: Wuerkaixi, Abudukelimu, et al.
Publicado: (2025)
por: Wuerkaixi, Abudukelimu, et al.
Publicado: (2025)
Better Generative Replay for Continual Federated Learning
por: Qi, Daiqing, et al.
Publicado: (2023)
por: Qi, Daiqing, et al.
Publicado: (2023)
Barlow Twins Deep Neural Network for Advanced 1D Drug-Target Interaction Prediction
por: Schuh, Maximilian G., et al.
Publicado: (2024)
por: Schuh, Maximilian G., et al.
Publicado: (2024)
DESIRE: Dynamic Knowledge Consolidation for Rehearsal-Free Continual Learning
por: Guo, Haiyang, et al.
Publicado: (2024)
por: Guo, Haiyang, et al.
Publicado: (2024)
'Si'multaneous 'S'patial-'T'emporal Message Passing for Dynamic Graph Representation Learning
por: Roy, Shubhajit, et al.
Publicado: (2026)
por: Roy, Shubhajit, et al.
Publicado: (2026)
Continual Learning for Adaptable Car-Following in Dynamic Traffic Environments
por: Chen, Xianda, et al.
Publicado: (2024)
por: Chen, Xianda, et al.
Publicado: (2024)
Large-Small Model Collaborative Framework for Federated Continual Learning
por: Yu, Hao, et al.
Publicado: (2025)
por: Yu, Hao, et al.
Publicado: (2025)
Explainability and Continual Learning meet Federated Learning at the Network Edge
por: Tsouparopoulos, Thomas, et al.
Publicado: (2025)
por: Tsouparopoulos, Thomas, et al.
Publicado: (2025)
Federated Continual Learning via Knowledge Fusion: A Survey
por: Yang, Xin, et al.
Publicado: (2023)
por: Yang, Xin, et al.
Publicado: (2023)
Personalized Federated Continual Learning via Multi-granularity Prompt
por: Yu, Hao, et al.
Publicado: (2024)
por: Yu, Hao, et al.
Publicado: (2024)
Federated Learning of Dynamic Bayesian Network via Continuous Optimization from Time Series Data
por: Chen, Jianhong, et al.
Publicado: (2024)
por: Chen, Jianhong, et al.
Publicado: (2024)
AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID Data
por: Tang, Jianheng, et al.
Publicado: (2025)
por: Tang, Jianheng, et al.
Publicado: (2025)
Shift Happens: Mixture of Experts based Continual Adaptation in Federated Learning
por: Bhope, Rahul Atul, et al.
Publicado: (2025)
por: Bhope, Rahul Atul, et al.
Publicado: (2025)
Closed-form merging of parameter-efficient modules for Federated Continual Learning
por: Salami, Riccardo, et al.
Publicado: (2024)
por: Salami, Riccardo, et al.
Publicado: (2024)
Masked Omics Modeling for Multimodal Representation Learning across Histopathology and Molecular Profiles
por: Robinet, Lucas, et al.
Publicado: (2025)
por: Robinet, Lucas, et al.
Publicado: (2025)
On Understanding of the Dynamics of Model Capacity in Continual Learning
por: Chakraborty, Supriyo, et al.
Publicado: (2025)
por: Chakraborty, Supriyo, et al.
Publicado: (2025)
Continuous Diffusion Transformers for Designing Synthetic Regulatory Elements
por: Liu, Jonathan, et al.
Publicado: (2026)
por: Liu, Jonathan, et al.
Publicado: (2026)
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks
por: Chakraborty, Biswadeep, et al.
Publicado: (2024)
por: Chakraborty, Biswadeep, et al.
Publicado: (2024)
Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-off
por: Lai, Song, et al.
Publicado: (2025)
por: Lai, Song, et al.
Publicado: (2025)
Optimization-Induced Dynamics of Lipschitz Continuity in Neural Networks
por: Luo, Róisín, et al.
Publicado: (2025)
por: Luo, Róisín, et al.
Publicado: (2025)
Condensation-Concatenation Framework for Dynamic Graph Continual Learning
por: Yan, Tingxu, et al.
Publicado: (2025)
por: Yan, Tingxu, et al.
Publicado: (2025)
Self-Controlled Dynamic Expansion Model for Continual Learning
por: Wu, Runqing, et al.
Publicado: (2025)
por: Wu, Runqing, et al.
Publicado: (2025)
CLeAN: Continual Learning Adaptive Normalization in Dynamic Environments
por: Marasco, Isabella, et al.
Publicado: (2026)
por: Marasco, Isabella, et al.
Publicado: (2026)
An Effective Dynamic Gradient Calibration Method for Continual Learning
por: Lin, Weichen, et al.
Publicado: (2024)
por: Lin, Weichen, et al.
Publicado: (2024)
SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices
por: Zhong, Zhengyi, et al.
Publicado: (2025)
por: Zhong, Zhengyi, et al.
Publicado: (2025)
Variational Bayes for Federated Continual Learning
por: Yao, Dezhong, et al.
Publicado: (2024)
por: Yao, Dezhong, et al.
Publicado: (2024)
Sketch-guided Image Inpainting with Partial Discrete Diffusion Process
por: Sharma, Nakul, et al.
Publicado: (2024)
por: Sharma, Nakul, et al.
Publicado: (2024)
E-CGL: An Efficient Continual Graph Learner
por: Guo, Jianhao, et al.
Publicado: (2024)
por: Guo, Jianhao, et al.
Publicado: (2024)
A Multivocal Literature Review on Privacy and Fairness in Federated Learning
por: Balbierer, Beatrice, et al.
Publicado: (2024)
por: Balbierer, Beatrice, et al.
Publicado: (2024)
Information as Structural Alignment: A Dynamical Theory of Continual Learning
por: Negulescu, Radu
Publicado: (2026)
por: Negulescu, Radu
Publicado: (2026)
Ejemplares similares
-
FrOoDo: Framework for Out-of-Distribution Detection
por: Stieber, Jonathan, et al.
Publicado: (2022) -
GAUDA: Generative Adaptive Uncertainty-guided Diffusion-based Augmentation for Surgical Segmentation
por: Frisch, Yannik, et al.
Publicado: (2025) -
ASMR: Angular Support for Malfunctioning Client Resilience in Federated Learning
por: Konstantin, Mirko, et al.
Publicado: (2025) -
Federated Continual Instruction Tuning
por: Guo, Haiyang, et al.
Publicado: (2025) -
FDRMFL:Multi-modal Federated Feature Extraction Model Based on Information Maximization and Contrastive Learning
por: Wu, Haozhe
Publicado: (2025)