Publications associées à Lecture performée

SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization

Olga Fink, Ismail Nejjar, Han Sun, Hao Dong

In real-world scenarios, achieving domain generalization (DG) presents significant challenges as models are required to generalize to unknown target distributions. Generalizing to unseen multi-modal distributions poses even greater difficulties due to the ...

2023

Maximum Radiation Efficiency of an Implantable Antenna: The Role of High-Order Modes

Anja Skrivervik, Mingxiang Gao, Jakub Liska

A combination of two numerical techniques of computational electromagnetics, namely, method of moments and vector spherical wave expansion, is used to show performance limitations on the radiation efficiency of implantable antennas and to efficiently resol ...

IEEE2023

Positive and Negative Critiquing for VAE-based Recommenders

Boi Faltings, Diego Matteo Antognini

Providing explanations for recommended items allows users to refine the recommendations by critiquing parts of the explanations. As a result of revisiting critiquing from the perspective of multimodal generative models, recent work has proposed M&Ms-VAE, w ...

2022

Cortical sensory processing across motivational states during goal-directed behavior

Carl Petersen, Georgios Foustoukos, Matthieu Pierre Auffret, Sami El-Boustani, Johannes Maria Mayrhofer, Maëlle Guyoton

Behavioral states can influence performance of goal-directed sensorimotor tasks. Yet, it is unclear how altered neuronal sensory representations in these states relate to task performance and learning. We trained water-restricted mice in a two-whisker disc ...

2022

An Analysis of Super-Net Heuristics in Weight-Sharing NAS

Mathieu Salzmann, Kaicheng Yu

Weight sharing promises to make neural architecture search (NAS) tractable even on commodity hardware. Existing methods in this space rely on a diverse set of heuristics to design and train the shared-weight backbone network, a.k.a. the super-net. Since he ...

IEEE COMPUTER SOC2022

Multiscale Representation Learning of Graph Data With Node Affinity

Pascal Frossard, Chenglin Li, Xing Gao

Graph neural networks have emerged as a popular and powerful tool for learning hierarchical representation of graph data. In complement to graph convolution operators, graph pooling is crucial for extracting hierarchical representation of data in graph neu ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

On the effectiveness of adversarial training against common corruptions

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Klim Kireev

The literature on robustness towards common corruptions shows no consensus on whether adversarial training can improve the performance in this setting. First, we show that, when used with an appropriately selected perturbation radius, ℓp adversarial traini ...

2021

Perspectives on Individual Animal Identification from Biology and Computer Vision

Alexander Mathis, Maxime Michel André Vidal

Identifying individual animals is crucial for many biological investigations. In response to some of the limitations of current identification methods, new automated computer vision approaches have emerged with strong performance. Here, we review current a ...

OXFORD UNIV PRESS INC2021

Dynamic Model Pruning with Feedback

Martin Jaggi, Sebastian Urban Stich, Luis Felipe Barba Flores, Tao Lin, Daniil Dmitriev

Deep neural networks often have millions of parameters. This can hinder their deployment to low-end devices, not only due to high memory requirements but also because of increased latency at inference. We propose a novel model compression method that gener ...

2020

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Lecture performée

SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization

Maximum Radiation Efficiency of an Implantable Antenna: The Role of High-Order Modes

Positive and Negative Critiquing for VAE-based Recommenders

Cortical sensory processing across motivational states during goal-directed behavior

An Analysis of Super-Net Heuristics in Weight-Sharing NAS

Montreux Co-Operative Culturelle. Une architecture de l'intelligence collective

Multiscale Representation Learning of Graph Data With Node Affinity

On the effectiveness of adversarial training against common corruptions

Perspectives on Individual Animal Identification from Biology and Computer Vision

Dynamic Model Pruning with Feedback

Graph Chatbot

Chattez avec Graph Search

An Analysis of Super-Net Heuristics in Weight-Sharing NAS

SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization

Perspectives on Individual Animal Identification from Biology and Computer Vision

Dynamic Model Pruning with Feedback

Maximum Radiation Efficiency of an Implantable Antenna: The Role of High-Order Modes

Cortical sensory processing across motivational states during goal-directed behavior

On the effectiveness of adversarial training against common corruptions

Montreux Co-Operative Culturelle. Une architecture de l'intelligence collective

Positive and Negative Critiquing for VAE-based Recommenders

Multiscale Representation Learning of Graph Data With Node Affinity