Publications associées à Least absolute deviations

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

Mathieu Salzmann, Alexandre Massoud Alahi, Megh Hiren Shukla

Deep heteroscedastic regression involves jointly optimizing the mean and covariance of the predicted distribution using the negative log-likelihood. However, recent works show that this may result in sub-optimal convergence due to the challenges associated ...

2024

Glenohumeral joint force prediction with deep learning

Dominique Pioletti, Alexandre Terrier, Patrick Goetti, Philippe Büchler

Deep learning models (DLM) are efficient replacements for computationally intensive optimization techniques. Musculoskeletal models (MSM) typically involve resource-intensive optimization processes for determining joint and muscle forces. Consequently, DLM ...

London2024

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

David Atienza Alonso, José Angel Miranda Calero, Jonathan Dan, Christodoulos Kechris

Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained as a data-driven inference problem offer promising solutions, they often un ...

2024

Range-separated hybrid functionals for accurate prediction of band gaps of extended systems

Alfredo Pasquarello, Stefano Falletta, Jing Yang

In this work, we systematically evaluate the accuracy in band gap prediction of range-separated hybrid functionals on a large set of semiconducting and insulating materials and carry out comparisons with the performance of their global counterparts. We obs ...

NATURE PORTFOLIO2023

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit

Ursula Röthlisberger, Justin Villard, Martin Peter Bircher

Second-order Moller-Plesset perturbation theory (MP2) is the most expedient wave function-based method for considering electron correlation in quantum chemical calculations and, as such, provides a cost-effective framework to assess the effects of basis se ...

Washington2023

Human-machine interface for two-dimensional steering control with the auricular muscles

Silvestro Micera, Solaiman Shokur, Daniel Jose Lins Leal Pinheiro

Human-machine interfaces (HMIs) can be used to decode a user's motor intention to control an external device. People that suffer from motor disabilities, such as spinal cord injury, can benefit from the uses of these interfaces. While many solutions can be ...

FRONTIERS MEDIA SA2023

Saddle-to-Saddle Dynamics in Diagonal Linear Networks

Nicolas Henri Bernard Flammarion, Scott William Pesme

In this paper we fully describe the trajectory of gradient flow over diagonal linear networks in the limit of vanishing initialisation. We show that the limiting flow successively jumps from a saddle of the training loss to another until reaching the minim ...

2023

Continuous corrected particle number concentration data in 10 sec resolution measured in the Swiss aerosol container using a whole air inlet during MOSAiC 2019/2020

Julia Schmale, Ivo Fabio Beck

This dataset contains corrected particle number concentration data measured during the year-long MOSAiC expedition from October 2019 to September 2020. Some periods of the measurements were affected by repeated step changes in the particle number concentra ...

EPFL Infoscience2023

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Least absolute deviations

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization

Glenohumeral joint force prediction with deep learning

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

Range-separated hybrid functionals for accurate prediction of band gaps of extended systems

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

Human-machine interface for two-dimensional steering control with the auricular muscles

Saddle-to-Saddle Dynamics in Diagonal Linear Networks

Continuous corrected particle number concentration data in 10 sec resolution measured in the Swiss aerosol container using a whole air inlet during MOSAiC 2019/2020

Graph Chatbot

Chattez avec Graph Search

Range-separated hybrid functionals for accurate prediction of band gaps of extended systems

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

Saddle-to-Saddle Dynamics in Diagonal Linear Networks

Human-machine interface for two-dimensional steering control with the auricular muscles

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

Glenohumeral joint force prediction with deep learning

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

Continuous corrected particle number concentration data in 10 sec resolution measured in the Swiss aerosol container using a whole air inlet during MOSAiC 2019/2020

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit