Publications de Pascal Frossard

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

Depth sensing is essential for intelligent computer vision applications, but it often suffers from low range precision and spatial resolution. To address this problem, we propose a novel framework that combines non-uniform sampling and reconstruction based ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

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

Pascal Frossard, Jacques Fellay, Vincent Jung

In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to many cellular processes. However, uncovering new mRNA functions is constrained by limitations of traditional biochemical and computational methods. In this Ro ...

NATURE PORTFOLIO2025

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

Pascal Frossard

Developing effective 360-degree (spherical) image compression techniques is crucial for technologies like virtual reality and automated driving. This paper advances the state-of-the-art in on-the-sphere learning (OSLO) for omnidirectional image compression ...

IEEE2025

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

Pascal Frossard

Institute of Electrical and Electronics Engineers (IEEE)2025

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

Pascal Frossard, Dimitri Nestor Alice Van De Ville, William Cappelletti, Ilaria Ricchi, Ekansh Sareen

The Graph Laplacian Mixture Model (GLMM) allows to infer multiple underlying graph structures from multivariate time series data. Given its effectiveness in identifying brain states from brain activity measured by functional magnetic resonance imaging (fMR ...

IEEE2025

Sequential Representation Learning via Static-Dynamic Conditional Disentanglement

Pascal Frossard

This paper explores self-supervised disentangled representation learning within sequential data, focusing on separating time-indep- endent and time-varying factors in videos. We propose a new model that breaks the usual independence assumption between thos ...

Springer Science and Business Media Deutschland GmbH2025

Equivariant 3D-conditional diffusion model for molecular linker design

Pascal Frossard, Bruno Emanuel Ferreira De Sousa Correia, Clément Arthur Yvon Vignac, Ilia Igashov, Arne Schneuing

Fragment-based drug discovery has been an effective paradigm in early-stage drug development. An open challenge in this area is designing linkers between disconnected molecular fragments of interest to obtain chemically relevant candidate drug molecules. I ...

2024

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

Pascal Frossard

Predicting the saliency map of a 360-degree video is the key for various downstream tasks, such as saliency-based compression and tile-based adaptive streaming. Besides static salient objects, the moving target will also contribute to the saliency map. The ...

2024

IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detection

Pascal Frossard

Bird's eye view (BEV) representation has emerged as a dominant solution for describing 3D space in autonomous driving scenarios. However, objects in the BEV representation typically exhibit small sizes, and the associated point cloud context is inherently ...

IEEE Computer Society2024

Tertiary Lymphoid Structures Generation Through Graph-Based Diffusion

Pascal Frossard, Ntorina Thanou

Graph-based representation approaches have been proven to be successful in the analysis of biomedical data due to their capability of capturing intricate dependencies between biological entities, such as the spatial organization of different cell types in ...

Springer International Publishing Ag2024

Adversarial Training for Jamming-Robust Channel Estimation in OFDM Systems

Pascal Frossard, Javier Alejandro Maroto Morales

Orthogonal frequency-division multiplexing (OFDM) is widely used to mitigate inter-symbol interference (ISI) from multipath fading. However, the open nature of wireless OFDM systems makes them vulnerable to jamming attacks. In this context, pilot jamming i ...

2024

Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction

Pascal Frossard, Emmanuel Abbé, Ntorina Thanou, Ivan-Daniel Sievering, Ortal Yona Senouf

Goal: In patients with coronary artery disease, the prediction of future cardiac events such as myocardial infarction (MI) remains a major challenge. In this work, we propose a novel anatomy-informed multimodal deep learning framework to predict future MI ...

2024

Hierarchical Training of Deep Neural Networks Using Early Exiting

Pascal Frossard, Liza Carol Andrea Dunbar, Ahmet Caner Yüzügüler, Yamin Sepehri

Deep neural networks (DNNs) provide state-of-the-art accuracy for vision tasks, but they require significant resources for training. Thus, they are trained on cloud servers far from the edge devices that acquire the data. This issue increases communication ...

Ieee-Inst Electrical Electronics Engineers Inc2024

SVGC-AVA: 360-Degree Video Saliency Prediction With Spherical Vector-Based Graph Convolution and Audio-Visual Attention

Pascal Frossard, Li Wei, Chenglin Li, Qin Yang, Yuelei Li

Viewers of 360-degree videos are provided with both visual modality to characterize their surrounding views and audio modality to indicate the sound direction. Though both modalities are important for saliency prediction, little work has been done by joint ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Online Network Source Optimization with Graph-Kernel MAB

Pascal Frossard

We propose Grab-UCB, a graph-kernelmulti-arms bandit algorithm to learn online the optimal source placement in large scale networks, such that the reward obtained from a priori unknown network processes is maximized. The uncertainty calls for online learni ...

Springer International Publishing Ag2023

DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications

Pascal Frossard, Ádám Dániel Ivánkay

Along with the successful deployment of deep neural networks in several application domains, the need to unravel the black-box nature of these networks has seen a significant increase recently. Several methods have been introduced to provide insight into t ...

Assoc Computational Linguistics-Acl2023

On the Granularity of Explanations in Model Agnostic NLP Interpretability

Pascal Frossard, Yves Rychener

Current methods for Black-Box NLP interpretability, like LIME or SHAP, are based on altering the text to interpret by removing words and modeling the Black-Box response. In this paper, we outline limitations of this approach when using complex BERT-based c ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

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

Pascal Frossard, Clémentine Léa Aguet

Blood pressure (BP) is a crucial biomarker giving valuable information regarding cardiovascular diseases but requires accurate continuous monitoring to maximize its value. In the effort of developing non-invasive, non-occlusive and continuous BP monitoring ...

PUBLIC LIBRARY SCIENCE2023

Stereo Confidence Estimation via Locally Adaptive Fusion and Knowledge Distillation

Pascal Frossard, Seungryong Kim

Stereo confidence estimation aims to estimate the reliability of the estimated disparity by stereo matching. Different from the previous methods that exploit the limited input modality, we present a novel method that estimates confidence map of an initial ...

IEEE COMPUTER SOC2023

Privacy-Preserving Image Acquisition for Neural Vision Systems

Pascal Frossard, Yamin Sepehri

Preserving privacy is a growing concern in our society where cameras are ubiquitous. In this work, we propose a trainable image acquisition method that removes the sensitive information in the optical domain before it reaches the image sensor. The method b ...

Ieee-Inst Electrical Electronics Engineers Inc2023