Response: Machine Learning Should Enrich, Not Replace, Human Deliberation in End-of-Life Decisions

G. Starke; L. Schopp; C. Meier; J. Baffou; D. Thanou et al. 

Learning Many Tasks via Weight-Space Geometry

Graph-Dictionary Signal Model for Sparse Representation of Multivariate Data

W. Cappelletti; P. Frossard 

Revisiting Automatic Data Curation for Vision Foundation Models in Digital Pathology

B. Chen; C. Vincent-Cuaz; L. A. Schoenpflug; M. Madeira; L. Fournier et al. 

A Fast Volumetric Capture and Reconstruction Pipeline for Dynamic Point Clouds and Gaussian Splats

A. Charisoudis; S. Croci; K. Y. Lam; P. Frossard; A. Smolic 

AI-Driven multi-view learning from CCTA for myocardial infarction diagnosis

J. Gwizdała; A. Salihu; O. Senouf; D. Meier; D. C. Rotzinger et al. 

Machine Learning–Based Patient Preference Prediction: A Proof of Concept

G. Starke; L. Schopp; C. Meier; J. Baffou; D. Thanou et al. 

CM-UNet: A Self-Supervised Learning-Based Model for Coronary Artery Segmentation in X-Ray Angiography

C. Challier; X. Sun; T. Mahendiran; O. Y. Senouf; B. De Bruyne et al. 

Physics-informed model of epileptic seizure dynamics

M. Ruch; A. Venkitaraman; O. Y. Senouf; P. Frossard 

Decoding the Interactions and Functions of Non-coding Rna with Artificial Intelligence

V. Jung; C. Vincent-Cuaz; C. Tumescheit; L. Fournier; M. Darsinou et al. 

Revealing Brain and Spinal Cord Functional Networks by Block-Structured Graph Laplacian Mixture Models

I. Ricchi; W. Cappelletti; E. Sareen; P. Frossard; D. Van De Ville 

OSLO-IC: On-the-Sphere Learned Omnidirectional Image Compression with Attention Modules and Spatial Context

P. Wawerek-López; N. M. Bidgoli; P. Frossard; A. Kaup; T. Maugey 

Extended pre-training of histopathology foundation models uncovers co-existing breast cancer archetypes characterized by RNA splicing or TGF-β dysregulation

L. M. Fournier; G. Haefliger; A. E. Vernhes; V. Jung; I. Letovanec et al. 

GraphTeacher: Transductive Fine-Tuning of Encoders through Graph Neural Networks

E. Koç; A. C. Aras; T. Alikasifoglu; A. Koç 

On the Role of Structure in Hierarchical Graph Neural Networks

L. Sbicego; S. Ogut; M. Madeira; Y. Qin; D. Thanou et al. 

Efficient Adaptation for Speech Technology

Sequential Representation Learning via Static-Dynamic Conditional Disentanglement

M. C. Simon; P. Frossard; C. D. Vleeschouwer 

Hierarchical Spherical CNNs with Lifting-Based Adaptive Wavelets for Pooling and Unpooling

M. Xu; C. Li; W. Dai; S. Chen; J. Zou et al. 

High-Quality Reconstruction of Depth Maps From Graph-Based Non-Uniform Sampling

J. Yang; W. Xu; Y. Hou; X. Ye; P. Frossard et al. 

PriPHiT: Privacy-Preserving Hierarchical Training of Deep Neural Networks

Y. Sepehri; P. Pad; P. Frossard; L. A. Dunbar 

Informed machine learning models for advancing cardiac disease prognosis

angioPy: an open-source, deep learning-driven tool for coronary artery segmentation

T. Mahendiran; D. Thanou; O. Y. Senouf; Y. Jamaa; S. Fournier et al. 

360Spred: Saliency Prediction for 360-Degree Videos Based on 3D Separable Graph Convolutional Networks

Q. Yang; W. Gao; C. Li; H. Wang; W. Dai et al. 

Hierarchical Training of Deep Neural Networks Using Early Exiting

Y. Sepehri; P. Pad; A. C. Yuzuguler; P. Frossard; A. Dunbar 

Future cardiovascular events prediction from invasive coronary angiography: A graph representation learning perspective

X. Sun; T. Belmpas; O. Y. Senouf; E. Abbé; P. Frossard et al. 

Equivariant 3D-conditional diffusion model for molecular linker design

I. Igashov; H. Stärk; C. Vignac; A. Schneuing; V. G. Satorras et al. 

Generative Modelling of Structurally Constrained Graphs

M. Madeira; C. Vignac; D. Thanou; P. Frossard 

The influence of data on adversarial robustness

Multi-Frequency Tracking via Group-Sparse Optimal Transport

I. Haasler; F. Elvander 

GRAPH-STRUCTURED TENSOR OPTIMIZATION FOR NONLINEAR DENSITY CONTROL AND MEAN FIELD GAMES

A. Ringh; I. Haasler; Y. Chen; J. Karlsson