Cover Image

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Saha, Pramit, Mishra, Divyanshu, Wagner, Felix, Kamnitsas, Konstantinos, Noble, J. Alison
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection
by: Saha, Pramit, et al.
Published: (2024)

F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics
by: Saha, Pramit, et al.
Published: (2024)

DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging
by: Wagner, Felix, et al.
Published: (2025)

FedAgentBench: Towards Automating Real-world Federated Medical Image Analysis with Server-Client LLM Agents
by: Saha, Pramit, et al.
Published: (2025)

Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities
by: Wagner, Felix, et al.
Published: (2024)

Picking the Right Specialist: Attentive Neural Process-based Selection of Task-Specialized Models as Tools for Agentic Healthcare Systems
by: Saha, Pramit, et al.
Published: (2026)

MCAT: Visual Query-Based Localization of Standard Anatomical Clips in Fetal Ultrasound Videos Using Multi-Tier Class-Aware Token Transformer
by: Mishra, Divyanshu, et al.
Published: (2025)

Self-supervised Learning of Echocardiographic Video Representations via Online Cluster Distillation
by: Mishra, Divyanshu, et al.
Published: (2025)

Self-supervised Normality Learning and Divergence Vector-guided Model Merging for Zero-shot Congenital Heart Disease Detection in Fetal Ultrasound Videos
by: Saha, Pramit, et al.
Published: (2025)

Coherent Hierarchical Multi-Label Learning to Defer for Medical Imaging
by: Strong, Joshua, et al.
Published: (2026)

Neural Collapse-Inspired Multi-Label Federated Learning under Label-Distribution Skew
by: Peng, Can, et al.
Published: (2025)

IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI
by: Liang, Ziyun, et al.
Published: (2024)

Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation
by: Wei, Ting, et al.
Published: (2025)

Heterogeneous Federated Reinforcement Learning Using Wasserstein Barycenters
by: Pereira, Luiz, et al.
Published: (2025)

Experience-Guided Self-Adaptive Cascaded Agents for Breast Cancer Screening and Diagnosis with Reduced Biopsy Referrals
by: Saha, Pramit, et al.
Published: (2026)

Modality-Agnostic Input Channels Enable Segmentation of Brain lesions in Multimodal MRI with Sequences Unavailable During Training
by: Addison, Anthony P., et al.
Published: (2025)

Federated Continual 3D Segmentation With Single-round Communication
by: Peng, Can, et al.
Published: (2025)

SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation
by: Zhu, Jiayuan, et al.
Published: (2024)

Identity-Free Deferral For Unseen Experts
by: Strong, Joshua, et al.
Published: (2025)

Fairness in Multi-Task Learning via Wasserstein Barycenters
by: Hu, François, et al.
Published: (2023)

Generalized Wasserstein Barycenters
by: Tornabene, Francesco, et al.
Published: (2024)

Wasserstein-Barycenter Consensus for Cooperative Multi-Agent Reinforcement Learning
by: Baheri, Ali
Published: (2025)

Differentially Private Wasserstein Barycenters
by: Gu, Anming, et al.
Published: (2025)

The Signed Wasserstein Barycenter Problem
by: Jacobs, Matt, et al.
Published: (2026)

Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection
by: Anthony, Harry, et al.
Published: (2024)

Adapted Wasserstein Barycenters of Gaussian Processes
by: Mattesini, Francesco, et al.
Published: (2026)

Doubly Regularized Entropic Wasserstein Barycenters
by: Chizat, Lénaïc
Published: (2023)

Wasserstein Barycenter Soft Actor-Critic
by: Shahrooei, Zahra, et al.
Published: (2025)

Gromov-Wasserstein Barycenters: The Analysis Problem
by: Martín, Rocío Díaz, et al.
Published: (2025)

pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models
by: Ghiasvand, Sajjad, et al.
Published: (2025)

Semi-Supervised Learning for Deep Causal Generative Models
by: Ibrahim, Yasin, et al.
Published: (2024)

The Promise of Analog Deep Learning: Recent Advances, Challenges and Opportunities
by: Datar, Aditya, et al.
Published: (2024)

Investigating Deep Learning Models for Ejection Fraction Estimation from Echocardiography Videos
by: Saranyan, Shravan, et al.
Published: (2025)

Scenario Tree Reduction via Wasserstein Barycenters
by: Mimouni, Daniel, et al.
Published: (2024)

Graph data augmentation with Gromow-Wasserstein Barycenters
by: Ponti, Andrea
Published: (2024)

Collaborative Bayesian Optimization via Wasserstein Barycenters
by: Zhan, Donglin, et al.
Published: (2025)

Geometry-Aware Decentralized Sinkhorn for Wasserstein Barycenters
by: Baheri, Ali, et al.
Published: (2025)

Towards Marginal Fairness Sliced Wasserstein Barycenter
by: Nguyen, Khai, et al.
Published: (2024)

Large Deviations Principle for Bures-Wasserstein Barycenters
by: Jaffe, Adam Quinn, et al.
Published: (2024)

Tangential Fixpoint Iterations for Gromov-Wasserstein Barycenters
by: Beier, Florian, et al.
Published: (2024)