b'EPFL'

research

∙ 06/30/2022

The Topological BERT: Transforming Attention into Topology for Natural Language Processing

In recent years, the introduction of the Transformer models sparked a re...

Ilan Perez, et al. ∙

research

∙ 10/02/2019

Using Image Priors to Improve Scene Understanding

Semantic segmentation algorithms that can robustly segment objects acros...

Brigit Schroeder, et al. ∙

research

∙ 12/18/2019

Inverse Graph Learning over Optimization Networks

Many inferential and learning tasks can be accomplished efficiently by m...

Vincenzo Matta, et al. ∙

research

∙ 11/25/2019

Estimating People Flows to Better Count them in Crowded Scenes

State-of-the-art methods for counting people in crowded scenes rely on d...

Weizhe Liu, et al. ∙

research

∙ 11/06/2021

Understanding Layer-wise Contributions in Deep Neural Networks through Spectral Analysis

Spectral analysis is a powerful tool, decomposing any function into simp...

Yatin Dandi, et al. ∙

research

∙ 04/06/2020

giotto-tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration

We introduce giotto-tda, a Python library that integrates high-performan...

Guillaume Tauzin, et al. ∙

research

∙ 06/24/2022

Learning sparse features can lead to overfitting in neural networks

It is widely believed that the success of deep networks lies in their ab...

Leonardo Petrini, et al. ∙

research

∙ 12/18/2019

Image Restoration using Plug-and-Play CNN MAP Denoisers

Plug-and-play denoisers can be used to perform generic image restoration...

Siavash Bigdeli, et al. ∙

research

∙ 06/16/2022

On the Surprising Behaviour of node2vec

Graph embedding techniques are a staple of modern graph learning researc...

Celia Hacker, et al. ∙

research

∙ 05/01/2019

Learn to synthesize and synthesize to learn

Attribute guided face image synthesis aims to manipulate attributes on a...

Behzad Bozorgtabar, et al. ∙

research

∙ 07/29/2021

Spatio-temporal estimation of wind speed and wind power using machine learning: predictions, uncertainty and technical potential

The growth of wind generation capacities in the past decades has shown t...

Federico Amato, et al. ∙

research

∙ 11/25/2019

Shape Reconstruction by Learning Differentiable Surface Representations

Generative models that produce point clouds have emerged as a powerful t...

Jan Bednařík, et al. ∙

research

∙ 06/19/2020

Self-Supervised Prototypical Transfer Learning for Few-Shot Classification

Most approaches in few-shot learning rely on costly annotated data relat...

Carlos Medina, et al. ∙

research

∙ 07/06/2021

NRST: Non-rigid Surface Tracking from Monocular Video

We propose an efficient method for non-rigid surface tracking from monoc...

Marc Habermann, et al. ∙

research

∙ 10/05/2021

Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation

In medical image segmentation, supervised deep networks' success comes a...

Devavrat Tomar, et al. ∙

research

∙ 06/27/2022

Positive-definite parametrization of mixed quantum states with deep neural networks

We introduce the Gram-Hadamard Density Operator (GHDO), a new deep neura...

Filippo Vicentini, et al. ∙

research

∙ 12/17/2019

Putting Ridesharing to the Test: Efficient and Scalable Solutions and the Power of Dynamic Vehicle Relocation

Ridesharing is a coordination problem in its core. Traditionally it has ...

Panayiotis Danassis, et al. ∙

research

∙ 05/31/2022

Generalised Implicit Neural Representations

We consider the problem of learning implicit neural representations (INR...

Daniele Grattarola, et al. ∙

research

∙ 07/18/2022

Neural Distributed Image Compression with Cross-Attention Feature Alignment

We propose a novel deep neural network (DNN) architecture for compressin...

Nitish Mital, et al. ∙

research

∙ 10/25/2021

SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checking

This paper describes SciClops, a method to help combat online scientific...

Panayiotis Smeros, et al. ∙

research

∙ 05/08/2021

On Linear Interpolation in the Latent Space of Deep Generative Models

The underlying geometrical structure of the latent space in deep generat...

Mike Yan Michelis, et al. ∙

research

∙ 08/20/2021

Self-Rule to Adapt: Generalized Multi-source Feature Learning Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Detection

Supervised learning is constrained by the availability of labeled data, ...

Christian Abbet, et al. ∙

research

∙ 01/14/2019

Self-Supervised Deep Active Accelerated MRI

We propose to simultaneously learn to sample and reconstruct magnetic re...

Kyong Hwan Jin, et al. ∙

research

∙ 12/14/2020

Decision-Making Algorithms for Learning and Adaptation with Application to COVID-19 Data

This work focuses on the development of a new family of decision-making ...

Stefano Marano, et al. ∙

research

∙ 09/08/2021

Active Learning by Acquiring Contrastive Examples

Common acquisition functions for active learning use either uncertainty ...

Katerina Margatina, et al. ∙

research

∙ 10/15/2021

Propagation on Multi-relational Graphs for Node Regression

Recent years have witnessed a rise in real-world data captured with rich...

Eda Bayram, et al. ∙

research

∙ 03/25/2020

Data Parallelism in Training Sparse Neural Networks

Network pruning is an effective methodology to compress large neural net...

Namhoon Lee, et al. ∙

research

∙ 08/21/2018

Isometric Transformation Invariant Graph-based Deep Neural Network

Learning transformation invariant representations of visual data is an i...

Renata Khasanova, et al. ∙

research

∙ 12/06/2018

Segmentation-driven 6D Object Pose Estimation

The most recent trend in estimating the 6D pose of rigid objects has bee...

Yinlin Hu, et al. ∙

research

∙ 03/15/2019

PifPaf: Composite Fields for Human Pose Estimation

We propose a new bottom-up method for multi-person 2D human pose estimat...

Sven Kreiss, et al. ∙

research

∙ 07/23/2019

Exploring Factors for Improving Low Resolution Face Recognition

State-of-the-art deep face recognition approaches report near perfect pe...

Omid Abdollahi Aghdam, et al. ∙

research

∙ 06/24/2022

From Tensor Network Quantum States to Tensorial Recurrent Neural Networks

We show that any matrix product state (MPS) can be exactly represented b...

Dian Wu, et al. ∙

research

∙ 02/07/2022

Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Countless signal processing applications include the reconstruction of s...

Jonathan Sauder, et al. ∙

research

∙ 06/05/2018

Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching

End-to-end deep-learning networks recently demonstrated extremely good p...

Stepan Tulyakov, et al. ∙

research

∙ 11/09/2018

Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks

We introduce a new scene graph generation method called image-level atte...

Guillaume Jaume, et al. ∙

research

∙ 03/13/2019

Neural Scene Decomposition for Multi-Person Motion Capture

Learning general image representations has proven key to the success of ...

Helge Rhodin, et al. ∙

research

∙ 11/26/2019

Using Depth for Pixel-Wise Detection of Adversarial Attacks in Crowd Counting

State-of-the-art methods for counting people in crowded scenes rely on d...

Weizhe Liu, et al. ∙

research

∙ 12/09/2021

A Shared Representation for Photorealistic Driving Simulators

A powerful simulator highly decreases the need for real-world tests when...

Saeed Saadatnejad, et al. ∙

research

∙ 10/02/2019

Joint Learning of Semantic Alignment and Object Landmark Detection

Convolutional neural networks (CNNs) based approaches for semantic align...

Sangryul Jeon, et al. ∙

research

∙ 06/12/2021

What can linearized neural networks actually say about generalization?

For certain infinitely-wide neural networks, the neural tangent kernel (...

Guillermo Ortiz-Jiménez, et al. ∙

research

∙ 07/29/2021

Mapping Vulnerable Populations with AI

Humanitarian actions require accurate information to efficiently delegat...

Benjamin Kellenberger, et al. ∙

research

∙ 03/26/2019

On the Performance of Exact Diffusion over Adaptive Networks

Various bias-correction methods such as EXTRA, DIGing, and exact diffusi...

Kun Yuan, et al. ∙

research

∙ 08/08/2019

Learning Vision-based Flight in Drone Swarms by Imitation

Decentralized drone swarms deployed today either rely on sharing of posi...

Fabian Schilling, et al. ∙

research

∙ 02/12/2020

Structure-Property Maps with Kernel Principal Covariates Regression

Data analysis based on linear methods, which look for correlations betwe...

Benjamin A. Helfrecht, et al. ∙

research

∙ 11/03/2020

BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration

Image restoration encompasses fundamental image processing tasks that ha...

Majed El Helou, et al. ∙

research

∙ 04/13/2021

Fast Hierarchical Games for Image Explanations

As modern complex neural networks keep breaking records and solving hard...

Jacopo Teneggi, et al. ∙

research

∙ 09/17/2021

Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules

One of the challenges faced by conversational agents is their inability ...

Forough Arabshahi, et al. ∙

research

∙ 10/05/2021

Top-N: Equivariant set and graph generation without exchangeability

We consider one-shot probabilistic decoders that map a vector-shaped pri...

Clément Vignac, et al. ∙

research

∙ 02/15/2022

Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition

In wearable-based human activity recognition (HAR) research, one of the ...

Jie Su, et al. ∙

research

∙ 07/03/2019

Cascade Attention Guided Residue Learning GAN for Cross-Modal Translation

Since we were babies, we intuitively develop the ability to correlate th...

Bin Duan, et al. ∙

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