Publications related to Disentangling feature and lazy training in deep neural networks

Phases of two-dimensional spinless lattice fermions with first-quantized deep neural-network quantum states

First-quantized deep neural network techniques are developed for analyzing strongly coupled fermionic systems on the lattice. Using a Slater-Jastrow-inspired ansatz which exploits deep residual networks with convolutional residual blocks, we approximately ...

AMER PHYSICAL SOC2020

Neural Anisotropy Directions

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Guillermo Ortiz Jimenez, Apostolos Modas

In this work, we analyze the role of the network architecture in shaping the inductive bias of deep classifiers. To that end, we start by focusing on a very simple problem, i.e., classifying a class of linearly separable distributions, and show that, depen ...

2020

Fluorescence lifetime imaging with a megapixel SPAD camera and neural network lifetime estimation

Edoardo Charbon, Claudio Bruschini, Ming-Lo Wu, Kazuhiro Morimoto

Fluorescence lifetime imaging microscopy (FLIM) is a key technology that provides direct insight into cell metabolism, cell dynamics and protein activity. However, determining the lifetimes of different fluorescent proteins requires the detection of a rela ...

NATURE RESEARCH2020

Single-Stage 6D Object Pose Estimation

Pascal Fua, Mathieu Salzmann, Wei Wang, Yinlin Hu

Most recent 6D pose estimation frameworks first rely on a deep network to establish correspondences between 3D object keypoints and 2D image locations and then use a variant of a RANSAC-based Perspective-n-Point (PnP) algorithm. This two-stage process, how ...

2020

Dynamic media content categorisation method

Sabine Süsstrunk, Mahmut Sami Arpa, Gabriel Albert Autes

The present invention concerns a method of classifying a media item into a user profile suitability class in a classification system comprising a set of pre-trained artificial neural networks. The method comprising: receiving (101) a media file; extracting ...

2020

Memory Augmented Neural Model for Incremental Session-based Recommendation

Boi Faltings, Fei Mi

Increasing concerns with privacy have stimulated interests in Session-based Recommendation (SR) using no personal data other than what is observed in the current browser session. Existing methods are evaluated in static settings which rarely occur in real- ...

2020

On the Relationship between Self-Attention and Convolutional Layers

Martin Jaggi, Andreas Loukas, Jean-Baptiste Francis Marie Juliette Cordonnier

Recent trends of incorporating attention mechanisms in vision have led re- searchers to reconsider the supremacy of convolutional layers as a primary build- ing block. Beyond helping CNNs to handle long-range dependencies, Ramachandran et al. (2019) showed ...

2020

AUTOMATIC DYSARTHRIC SPEECH DETECTION EXPLOITING PAIRWISE DISTANCE-BASED CONVOLUTIONAL NEURAL NETWORKS

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria. In this paper we propose a novel automatic dysarthric speech detection approach based on analy ...

Idiap2020

Shape Reconstruction by Learning Differentiable Surface Representations

Pascal Fua, Mathieu Salzmann, Shaifali Parashar, Jan Bednarík, Erhan Gündogdu

Generative models that produce point clouds have emerged as a powerful tool to represent 3D surfaces, and the best current ones rely on learning an ensemble of parametric representations. Unfortunately, they offer no control over the deformations of the su ...

2020

Square Attack: a query-efficient black-box adversarial attack via random search

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

We propose the Square Attack, a new score-based black-box

l_2

and

l_\infty

adversarial attack that does not rely on local gradient information and thus is not affected by gradient masking. The Square Attack is based on a randomized search scheme where ...

2020

Disentangling feature and lazy training in deep neural networks

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Phases of two-dimensional spinless lattice fermions with first-quantized deep neural-network quantum states

Neural Anisotropy Directions

Fluorescence lifetime imaging with a megapixel SPAD camera and neural network lifetime estimation

Single-Stage 6D Object Pose Estimation

Dynamic media content categorisation method

Memory Augmented Neural Model for Incremental Session-based Recommendation

On the Relationship between Self-Attention and Convolutional Layers

AUTOMATIC DYSARTHRIC SPEECH DETECTION EXPLOITING PAIRWISE DISTANCE-BASED CONVOLUTIONAL NEURAL NETWORKS

Shape Reconstruction by Learning Differentiable Surface Representations

Square Attack: a query-efficient black-box adversarial attack via random search

Memory Augmented Neural Model for Incremental Session-based Recommendation

Fluorescence lifetime imaging with a megapixel SPAD camera and neural network lifetime estimation

Phases of two-dimensional spinless lattice fermions with first-quantized deep neural-network quantum states

Dynamic media content categorisation method

AUTOMATIC DYSARTHRIC SPEECH DETECTION EXPLOITING PAIRWISE DISTANCE-BASED CONVOLUTIONAL NEURAL NETWORKS

Single-Stage 6D Object Pose Estimation

Neural Anisotropy Directions

On the Relationship between Self-Attention and Convolutional Layers

Shape Reconstruction by Learning Differentiable Surface Representations

Square Attack: a query-efficient black-box adversarial attack via random search