Copertina

Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Sun, Susu, Woerner, Stefano, Maier, Andreas, Koch, Lisa M., Baumgartner, Christian F.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Navigating Data Scarcity using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging
di: Woerner, Stefano, et al.
Pubblicazione: (2024)

A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset
di: Woerner, Stefano, et al.
Pubblicazione: (2024)

Universal Algorithm-Implicit Learning
di: Woerner, Stefano, et al.
Pubblicazione: (2026)

Prototype-Based Multiple Instance Learning for Gigapixel Whole Slide Image Classification
di: Sun, Susu, et al.
Pubblicazione: (2025)

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

Exploiting Inherent Class Label: Towards Robust Scribble Supervised Semantic Segmentation
di: Zhang, Xinliang, et al.
Pubblicazione: (2025)

Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training
di: Xie, Ming-Kun, et al.
Pubblicazione: (2024)

AttriPrompt: Dynamic Prompt Composition Learning for CLIP
di: Zhan, Qiqi, et al.
Pubblicazione: (2025)

AttriBE: Quantifying Attribute Expressivity in Body Embeddings for Recognition and Identification
di: Pal, Basudha, et al.
Pubblicazione: (2026)

FASR-Net: Unsupervised Shadow Removal Leveraging Inherent Frequency Priors
di: Lin, Tao, et al.
Pubblicazione: (2025)

Conformal Performance Range Prediction for Segmentation Output Quality Control
di: Wundram, Anna M., et al.
Pubblicazione: (2024)

Subgroup Performance Analysis in Hidden Stratifications
di: Bissoto, Alceu, et al.
Pubblicazione: (2025)

AttriCLIP: A Non-Incremental Learner for Incremental Knowledge Learning
di: Wang, Runqi, et al.
Pubblicazione: (2023)

Overcoming Common Flaws in the Evaluation of Selective Classification Systems
di: Traub, Jeremias, et al.
Pubblicazione: (2024)

X-SiT: Inherently Interpretable Surface Vision Transformers for Dementia Diagnosis
di: Bongratz, Fabian, et al.
Pubblicazione: (2025)

An Interpretable Local Editing Model for Counterfactual Medical Image Generation
di: Min, Hyungi, et al.
Pubblicazione: (2026)

AttriCtrl: Fine-Grained Control of Aesthetic Attribute Intensity in Diffusion Models
di: Chen, Die, et al.
Pubblicazione: (2025)

AttriStory: Fine-grained Attribute Realization for Visual Storytelling with Diffusion Models
di: Sreenivas, Manogna, et al.
Pubblicazione: (2026)

LMPT: Prompt Tuning with Class-Specific Embedding Loss for Long-tailed Multi-Label Visual Recognition
di: Xia, Peng, et al.
Pubblicazione: (2023)

nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation
di: Isensee, Fabian, et al.
Pubblicazione: (2024)

Dual-View Alignment Learning with Hierarchical-Prompt for Class-Imbalance Multi-Label Classification
di: Huang, Sheng, et al.
Pubblicazione: (2025)

Improving Interpretability and Accuracy in Neuro-Symbolic Rule Extraction Using Class-Specific Sparse Filters
di: Padalkar, Parth, et al.
Pubblicazione: (2025)

B-cos Alignment for Inherently Interpretable CNNs and Vision Transformers
di: Böhle, Moritz, et al.
Pubblicazione: (2023)

AIM: Amending Inherent Interpretability via Self-Supervised Masking
di: Alshami, Eyad, et al.
Pubblicazione: (2025)

Gesture Classification in Artworks Using Contextual Image Features
di: Hussian, Azhar, et al.
Pubblicazione: (2024)

Enhanced Multi-Class Classification of Gastrointestinal Endoscopic Images with Interpretable Deep Learning Model
di: Kamble, Astitva, et al.
Pubblicazione: (2025)

Rebalancing Multi-Label Class-Incremental Learning
di: Du, Kaile, et al.
Pubblicazione: (2024)

Imitating Radiological Scrolling: A Global-Local Attention Model for 3D Chest CT Volumes Multi-Label Anomaly Classification
di: Di Piazza, Theo, et al.
Pubblicazione: (2025)

Multi-class Seismic Building Damage Assessment from InSAR Imagery using Quadratic Variational Causal Bayesian Inference
di: Li, Xuechun, et al.
Pubblicazione: (2025)

Multi-Plane Vision Transformer for Hemorrhage Classification Using Axial and Sagittal MRI Data
di: Das, Badhan Kumar, et al.
Pubblicazione: (2025)

GS-Net: Global Self-Attention Guided CNN for Multi-Stage Glaucoma Classification
di: Das, Dipankar, et al.
Pubblicazione: (2024)

Classification Matters: Improving Video Action Detection with Class-Specific Attention
di: Lee, Jinsung, et al.
Pubblicazione: (2024)

Positive Label Is All You Need for Multi-Label Classification
di: Yuan, Zhixiang, et al.
Pubblicazione: (2023)

AttriHuman-3D: Editable 3D Human Avatar Generation with Attribute Decomposition and Indexing
di: Yang, Fan, et al.
Pubblicazione: (2023)

MCANet: A Multi-Scale Class-Specific Attention Network for Multi-Label Post-Hurricane Damage Assessment using UAV Imagery
di: Liu, Zhangding, et al.
Pubblicazione: (2025)

B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable
di: Arya, Shreyash, et al.
Pubblicazione: (2024)

Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability
di: Bhalla, Usha, et al.
Pubblicazione: (2023)

MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor Classification
di: Li, Binghua, et al.
Pubblicazione: (2024)

Class-wise Autoencoders Measure Classification Difficulty And Detect Label Mistakes
di: Marks, Jacob, et al.
Pubblicazione: (2024)

DocVCE: Diffusion-based Visual Counterfactual Explanations for Document Image Classification
di: Saifullah, Saifullah, et al.
Pubblicazione: (2025)