:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Salahuddin, Suaiba Amina, Dorszewski, Teresa, Martiniussen, Marit Almenning, Hovda, Tone, Portaluri, Antonio, Thrun, Solveig, Kampffmeyer, Michael, Wetzer, Elisabeth, Wickstrøm, Kristoffer, Jenssen, Robert
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2509.21102
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
by: Thrun, Solveig, et al.
Published: (2025)

Keypoint Counting Classifiers: Turning Vision Transformers into Self-Explainable Models Without Training
by: Wickstrøm, Kristoffer, et al.
Published: (2025)

The Impact of Longitudinal Mammogram Alignment on Breast Cancer Risk Assessment
by: Thrun, Solveig, et al.
Published: (2025)

From Colors to Classes: Emergence of Concepts in Vision Transformers
by: Dorszewski, Teresa, et al.
Published: (2025)

Fast Voxel-Wise Kinetic Modeling in Dynamic PET using a Physics-Informed CycleGAN
by: Salomonsen, Christian, et al.
Published: (2025)

REPEAT: Improving Uncertainty Estimation in Representation Learning Explainability
by: Wickstrøm, Kristoffer K., et al.
Published: (2024)

Physics-Informed Deep Learning for Improved Input Function Estimation in Motion-Blurred Dynamic [${}^{18}$F]FDG PET Images
by: Salomonsen, Christian, et al.
Published: (2025)

VMRA-MaR: An Asymmetry-Aware Temporal Framework for Longitudinal Breast Cancer Risk Prediction
by: Sun, Zijun, et al.
Published: (2025)

A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal $\left[^{18}\text{F}\right]$FDG PET imaging
by: Salomonsen, Christian, et al.
Published: (2025)

Random Window Augmentations for Deep Learning Robustness in CT and Liver Tumor Segmentation
by: Østmo, Eirik A., et al.
Published: (2025)

Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography
by: Ghosh, Shantanu, et al.
Published: (2024)

Mammo-CLIP: Leveraging Contrastive Language-Image Pre-training (CLIP) for Enhanced Breast Cancer Diagnosis with Multi-view Mammography
by: Chen, Xuxin, et al.
Published: (2024)

FLEXtime: Filterbank learning to explain time series
by: Brüsch, Thea, et al.
Published: (2024)

NOFE - Neural Operator Function Embedding
by: Uebbing, Lars, et al.
Published: (2026)

FreqRISE: Explaining time series using frequency masking
by: Brüsch, Thea, et al.
Published: (2024)

MammoWise: Multi-Model Local RAG Pipeline for Mammography Report Generation
by: Jahangir, Raiyan, et al.
Published: (2026)

MammoClean: Toward Reproducible and Bias-Aware AI in Mammography through Dataset Harmonization
by: Zafari, Yalda, et al.
Published: (2025)

Connecting Concept Convexity and Human-Machine Alignment in Deep Neural Networks
by: Dorszewski, Teresa, et al.
Published: (2024)

Transformer-Based Explainable Deep Learning for Breast Cancer Detection in Mammography: The MammoFormer Framework
by: Peter, Ojonugwa Oluwafemi Ejiga, et al.
Published: (2025)

SuperCM: Improving Semi-Supervised Learning and Domain Adaptation through differentiable clustering
by: Singh, Durgesh, et al.
Published: (2025)

In-hoc Concept Representations to Regularise Deep Learning in Medical Imaging
by: Corbetta, Valentina, et al.
Published: (2025)

From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation
by: Wickstrøm, Kristoffer, et al.
Published: (2024)

Mammo-Mamba: A Hybrid State-Space and Transformer Architecture with Sequential Mixture of Experts for Multi-View Mammography
by: Bayatmakou, Farnoush, et al.
Published: (2025)

Leveraging tensor kernels to reduce objective function mismatch in deep clustering
by: Trosten, Daniel J., et al.
Published: (2020)

Supercm: Revisiting Clustering for Semi-Supervised Learning
by: Singh, Durgesh, et al.
Published: (2025)

Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
by: Mancisidor, Rogelio A, et al.
Published: (2025)

MITOCHONDRIAL GENES AND ISOPOD PHYLOGENY (PERACARIDA: ISOPODA)
by: Wetzer, R
Published: (2002)

Mammo-Clustering: Context Clustering based Multi-view Tri Level Information Fusion for Lesion Location and Classification in Mammography
by: Yang, Shilong, et al.
Published: (2025)

Mammo-Clustering: A Multi-views Tri-level Information Fusion Context Clustering Framework for Localization and Classification in Mammography
by: Yang, Shilong, et al.
Published: (2024)

Convexity-based Pruning of Speech Representation Models
by: Dorszewski, Teresa, et al.
Published: (2024)

Optimization‐based pore network modeling approach for determination of hydraulic conductivity function of granular soils
by: Suaiba Mufti, et al.
Published: (2024)

Mammo-SAE: Interpreting Breast Cancer Concept Learning with Sparse Autoencoders
by: Nakka, Krishna Kanth
Published: (2025)

Projection-Based Clustering through Self-Organization and Swarm Intelligence: Combining Cluster Analysis with the Visualization of High-Dimensional Data
by: Christoph Thrun, Michael
Published: (2018)

Self-Organization and Swarm Intelligence Combining Cluster Analysis with the Visualization of High-Dimensional Data
by: Michael Christoph Thrun

WickstromLab/Punovuori-et-al.-Cell-2024: Punovuori et al., Cell 2024; Kaivola et al., Nat Materials 2025
by: WickströmLab
Published: (2025)

ProPy: Building Interactive Prompt Pyramids upon CLIP for Partially Relevant Video Retrieval
by: Pan, Yi, et al.
Published: (2025)

WiseLVAM: A Novel Framework For Left Ventricle Automatic Measurements
by: Singh, Durgesh Kumar, et al.
Published: (2025)

A Symphony of Fire, Ice, and Fog: How Leaders' Interpersonal Styles Shape Psychological Needs and Motivation
by: Leoni van der Vaart, et al.
Published: (2025)

How Redundant Is the Transformer Stack in Speech Representation Models?
by: Dorszewski, Teresa, et al.
Published: (2024)

MAM-CLIP: Vision-Language Pretraining on Mammography Atlases for BI-RADS Classification
by: Gulluk, Halil Ibrahim, et al.
Published: (2026)