Imagen de Portada

M4: Multi-Proxy Multi-Gate Mixture of Experts Network for Multiple Instance Learning in Histopathology Image Analysis

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Junyu, Zhang, Ye, Shu, Wen, Feng, Xiaobing, Wang, Yingchun, Yan, Pengju, Li, Xiaolin, Sha, Chulin, He, Min
Formato:	Preprint
Publicado:	2024
Materias:	Computer Vision and Pattern Recognition
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

STAMP: Multi-pattern Attention-aware Multiple Instance Learning for STAS Diagnosis in Multi-center Histopathology Images
por: Pan, Liangrui, et al.
Publicado: (2025)

RetMIL: Retentive Multiple Instance Learning for Histopathological Whole Slide Image Classification
por: Chu, Hongbo, et al.
Publicado: (2024)

Spatiotemporal-Untrammelled Mixture of Experts for Multi-Person Motion Prediction
por: Yin, Zheng, et al.
Publicado: (2025)

Integrating Multi-view Analysis: Multi-view Mixture-of-Expert for Textual Personality Detection
por: Zhu, Haohao, et al.
Publicado: (2024)

Advancing Robust Underwater Acoustic Target Recognition through Multi-task Learning and Multi-Gate Mixture-of-Experts
por: Xie, Yuan, et al.
Publicado: (2024)

Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing Images
por: Liu, Ye, et al.
Publicado: (2021)

MoCTEFuse: Illumination-Gated Mixture of Chiral Transformer Experts for Multi-Level Infrared and Visible Image Fusion
por: Jinfu, Li, et al.
Publicado: (2025)

SAGE: Shape-Adapting Gated Experts for Adaptive Histopathology Image Segmentation
por: Thai, Gia Huy, et al.
Publicado: (2025)

Multiple Instance Learning Framework with Masked Hard Instance Mining for Gigapixel Histopathology Image Analysis
por: Tang, Wenhao, et al.
Publicado: (2025)

Semi-MoE: Mixture-of-Experts meets Semi-Supervised Histopathology Segmentation
por: Vu, Nguyen Lan Vi, et al.
Publicado: (2025)

Mixture of Mini Experts: Overcoming the Linear Layer Bottleneck in Multiple Instance Learning
por: Shao, Daniel, et al.
Publicado: (2026)

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification
por: Bai, Yu, et al.
Publicado: (2025)

AI Psychometrics: Evaluating the Psychological Reasoning of Large Language Models with Psychometric Validities
por: Li, Yibai, et al.
Publicado: (2026)

MSME: A Multi-Stage Multi-Expert Framework for Zero-Shot Stance Detection
por: Zhang, Yuanshuo, et al.
Publicado: (2025)

Cracking Instance Jigsaw Puzzles: An Alternative to Multiple Instance Learning for Whole Slide Image Analysis
por: Chen, Xiwen, et al.
Publicado: (2025)

Continual Multiple Instance Learning with Enhanced Localization for Histopathological Whole Slide Image Analysis
por: Lee, Byung Hyun, et al.
Publicado: (2025)

Multi-Head Mixture-of-Experts
por: Wu, Xun, et al.
Publicado: (2024)

Adaptive Multi-Scale Integration Unlocks Robust Cell Annotation in Histopathology Images
por: Xu, Yinuo, et al.
Publicado: (2025)

xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology
por: Hense, Julius, et al.
Publicado: (2024)

Multi-modal Dynamic Proxy Learning for Personalized Multiple Clustering
por: Xu, Jinfeng, et al.
Publicado: (2025)

Gated Ensemble of Spatio-temporal Mixture of Experts for Multi-task Learning in Ride-hailing System
por: Rahman, M. H., et al.
Publicado: (2020)

Multi-Subspace Multi-Modal Modeling for Diffusion Models: Estimation, Convergence and Mixture of Experts
por: Yang, Ruofeng, et al.
Publicado: (2026)

Dynamic Adaptive Shared Experts with Grouped Multi-Head Attention Mixture of Experts
por: Li, Cheng, et al.
Publicado: (2025)

GateBreaker: Gate-Guided Attacks on Mixture-of-Expert LLMs
por: Wu, Lichao, et al.
Publicado: (2025)

TAG-MoE: Task-Aware Gating for Unified Generative Mixture-of-Experts
por: Xu, Yu, et al.
Publicado: (2026)

Sparse-Dense Mixture of Experts Adapter for Multi-Modal Tracking
por: Zhu, Yabin, et al.
Publicado: (2026)

Multi-residual Mixture of Experts Learning for Cooperative Control in Multi-vehicle Systems
por: Jayawardana, Vindula, et al.
Publicado: (2025)

Detecting Scarce and Sparse Anomalous: Solving Dual Imbalance in Multi-Instance Learning
por: Jia, Lin-Han, et al.
Publicado: (2025)

Arctic Sea Ice Image Super-Resolution Based on Multi-Scale Convolution and Dual-Gating Mechanism
por: Fang, Zhaomin, et al.
Publicado: (2024)

Multi-level Mixture of Experts for Multimodal Entity Linking
por: Hu, Zhiwei, et al.
Publicado: (2025)

Meta-Reinforcement Learning With Mixture of Experts for Generalizable Multi Access in Heterogeneous Wireless Networks
por: Liu, Zhaoyang, et al.
Publicado: (2024)

Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts
por: Nguyen, Huy, et al.
Publicado: (2023)

On Bayesian Softmax-Gated Mixture-of-Experts Models
por: Bariletto, Nicola, et al.
Publicado: (2026)

Convergence Rates for Softmax Gating Mixture of Experts
por: Nguyen, Huy, et al.
Publicado: (2025)

Gaussian Process-Gated Hierarchical Mixtures of Experts
por: Liu, Yuhao, et al.
Publicado: (2023)

Label-free Concept Based Multiple Instance Learning for Gigapixel Histopathology
por: Sun, Susu, et al.
Publicado: (2025)

Toward Effective Multi-Domain Rumor Detection in Social Networks Using Domain-Gated Mixture-of-Experts
por: Sheikhqoraei, Mohadeseh, et al.
Publicado: (2026)

Adaptive Shared Experts with LoRA-Based Mixture of Experts for Multi-Task Learning
por: Yang, Minghao, et al.
Publicado: (2025)

Multi-Task Dense Prediction Fine-Tuning with Mixture of Fine-Grained Experts
por: Xu, Yangyang, et al.
Publicado: (2025)

MsaMIL-Net: An End-to-End Multi-Scale Aware Multiple Instance Learning Network for Efficient Whole Slide Image Classification
por: Wen, Jiangping, et al.
Publicado: (2025)