Recent Publications

Stereo Confidence Estimation via Locally Adaptive Fusion and Knowledge Distillation

S. Kim; S. Kim; D. Min; P. Frossard; K. Sohn 

Blood pressure monitoring during anesthesia induction using PPG morphology features and machine learning

C. Aguet; J. Jorge; J. Van Zaen; M. Proenca; G. Bonnier et al. 

Estimating and Improving the Robustness of Attributions in Text

On the Granularity of Explanations in Model Agnostic NLP Interpretability

Y. Rychener; X. Renard; D. Seddah; P. Frossard; M. Detyniecki 

Graph Signal Separation Based on Smoothness or Sparsity in the Frequency Domain

S. Mohammadi; M. Babaie-Zadeh; D. Thanou 

Hardware-Software Co-design for Improved Resource Utilization in DNN Accelerators

Deep learning-based prediction of future myocardial infarction using invasive coronary angiography: a feasibility study

T. Mahendiran; D. Thanou; O. Senouf; D. Meier; N. Dayer et al. 

Anatomy-informed multimodal learning for myocardial infarction prediction

I-D. Sievering; O. Y. Senouf; T. Mahendiran; D. Nanchen; S. Fournier et al. 

Attention-based learning of views fusion applied to myocardial infarction diagnosis from x-ray CT

J. J. Gwizdala; O. Y. Senouf; D. Auberson; D. Meier; D. Rotzinger et al. 

Interpretable temporal-spatial graph attention network for multi-site PV power forecasting

J. Simeunovic; B. Schubnel; P-J. Alet; R. E. Carrillo; P. Frossard 

Landmarking for Navigational Streaming of Stored High-Dimensional Media

Y. Yuan; G. Cheung; P. Frossard; H. V. Zhao; J. Huang 

Post Hoc Explainability for Time Series Classification Toward a signal processing perspective

R. Mochaourab; A. Venkitaraman; I. Samsten; P. Papapetrou; C. R. Rojas 

Dynamics of functional network organization through graph mixture learning

I. Ricchi; A. Tarun; H. P. Maretic; P. Frossard; D. Van De Ville 

Spatio-Temporal Graph Neural Networks for Multi-Site PV Power Forecasting

J. Simeunovic; B. Schubnel; P-J. Alet; R. E. Carrillo 

Impulsive noise removal via a blind CNN enhanced by an iterative post-processing

S. Sadrizadeh; H. Otroshi-Shahreza; F. Marvasti 

Equivariant Diffusion for Molecule Generation in 3D

E. Hoogeboom; V. G. Satorras; C. Vignac; M. Welling 

fGOT: Graph Distances Based on Filters and Optimal Transport

H. P. Maretic; M. El Gheche; G. Chierchia; P. Frossard 

PRIME: A Few Primitives Can Boost Robustness to Common Corruptions

A. Modas; R. Rade; G. Ortiz-Jimenez; S-M. Moosavi-Dezfooli; P. Frossard 

Data augmentation with mixtures of max-entropy transformations for filling-level classification

A. Modas; A. Cavallaro; P. Frossard 

Adversarial training with informed data selection

M. O. K. Mendonca; J. Maroto; P. Frossard; P. S. R. Diniz 

SafeAMC: Adversarial training for robust modulation classification models

J. Maroto; G. Bovet; P. Frossard 

A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios

A. L. Perales Gomez; L. Fernandez Maimo; F. J. Garcia Clemente; J. A. Maroto Morales; A. Huertas Celdran et al. 

U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search

A. C. Yuzuguler; N. Dimitriadis; P. Frossard 

A Structured Dictionary Perspective on Implicit Neural Representations

G. Yuce; G. Ortiz-Jimenez; B. Besbinar; P. Frossard 

Block-Sparse Adversarial Attack To Fool Transformer-Based Text Classifiers

S. Sadrizadeh; L. Dolamic; P. Frossard 

Distributed Graph Learning With Smooth Data Priors

I. C. M. Nobre; M. El Gheche; P. Frossard 

Annihilation Filter Approach For Estimating Graph Dynamics From Diffusion Processes

A. Venkitaraman; P. Frossard 

Quantization for Distributed Processing and Learning of Structured Data

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression

N. M. Bidgoli; R. G. d. A. Azevedo; T. Maugey; A. Roumy; P. Frossard