Publications related to Mean percentage error

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

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

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

Tobias Kober, Davide Piccini

Purpose: To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-enco ...

Wiley2023

Statistical limits of dictionary learning: Random matrix theory and the spectral replica method

Nicolas Macris, Jean François Emmanuel Barbier

We consider increasingly complex models of matrix denoising and dictionary learning in the Bayes-optimal setting, in the challenging regime where the matrices to infer have a rank growing linearly with the system size. This is in contrast with most existin ...

AMER PHYSICAL SOC2022

Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation

Jean-Marc Vesin, Adrian Luca, Etienne Pruvot

Background: Signal processing tools are required to efficiently analyze data collected in body-surface-potential map (BSPM) recordings. A limited number of such tools exist for studying persistent atrial fibrillation (persAF). We propose two novel, spatiot ...

FRONTIERS MEDIA SA2022

A Machine Learning-based Framework for Forecasting Sales of New Products With Short Life Cycles Using Deep Neural Networks

Ralf Seifert, Yara Kayyali El Alem

Demand forecasting is becoming increasingly important as firms launch new products with short life cycles more frequently. This paper provides a framework based on state-of-the-art techniques that enables firms to use quantitative methods to forecast sales ...

2022

Accurate and efficient band-gap predictions for metal halide perovskites at finite temperature

Alfredo Pasquarello, Aleksei Tal, Haiyuan Wang, Patrick Gono, Thomas Bischoff

We develop a computationally efficient scheme to accurately determine finite-temperature band gaps for metal halide perovskites belonging to the class ABX(3) (A = Rb, Cs; B = Ge, Sn, Pb; and X = F, Cl, Br, I). First, an initial estimate of the band gap is ...

NATURE PORTFOLIO2022

Worldwide performance evaluation of ground surface reflectance models

Christophe Ballif, Pierre-Jean Alet, Arttu Matias Tuomiranta

To improve the accuracy of bifacial gain estimation, recent radiative models of solar energy systems have abandoned the traditional assumption of isotropic ground-reflected radiance. However, surface reflectance itself is still commonly considered as a con ...

2021

Discrete-Choice Mining of Social Processes

Victor Kristof

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

EPFL2021

Differential Entropy of the Conditional Expectation under Gaussian Noise

Michael Christoph Gastpar, Alper Köse, Ahmet Arda Atalik

This paper considers an additive Gaussian noise channel with arbitrarily distributed finite variance input signals. It studies the differential entropy of the minimum mean-square error (MMSE) estimator and provides a new lower bound which connects the diff ...

IEEE2021

Numerical Weather Prediction and Artificial Neural Network Coupling for Wind Energy Forecast

Fernando Porté Agel, Jiannong Fang, Lorenzo Donadio

In the past two decades, wind energy has been under fast development worldwide. The dramatic increase of wind power penetration in electricity production has posed a big challenge to grid integration due to the high uncertainty of wind power. Accurate real ...

2021

An automated calibration framework and open source tools for 3D lake hydrodynamic models

Alfred Johny Wüest, Damien Bouffard, Andrea Cimatoribus, Theo Baracchini

Understanding lake dynamics is crucial to provide scientifically credible information for ecosystem management. In this context, three-dimensional hydrodynamic models are a key information source to assess critical but often subtle changes in lake dynamics ...

2020

Evaluating salient object detection in natural images with multiple objects having multi-level saliency

Sabine Süsstrunk, Gökhan Yildirim

Salient object detection is evaluated using binary ground truth (GT) with the labels being salient object class and background. In this study, the authors corroborate based on three subjective experiments on a novel image dataset that objects in natural im ...

2020

Folded-Tube Soft Pneumatic Actuators for Bending

Wyatt Marshall Felt

This article presents a model and experimental results for a new class of bending soft pneumatic actuators (SPAs) made from a single section of thin-walled flexible tubing. The actuator is formed by creasing the tubing into fin-like rectangular folds and i ...

MARY ANN LIEBERT, INC2019

Chemical machine learning with kernels: The impact of loss functions

Volkan Cevher, Quoc Tran Dinh, Sandip De, Junhong Lin, Van Quang Nguyen

Machine learning promises to accelerate materials discovery by allowing computational efficient property predictions from a small number of reference calculations. As a result, the literature has spent a considerable effort in designing representations tha ...

2019

Locomotion and cadence detection using a single trunk-fixed accelerometer: validity for children with cerebral palsy in daily life-like conditions

Kamiar Aminian, Anisoara Ionescu, Lena Carcreff, Stéphane Armand

BACKGROUND: Physical therapy interventions for ambulatory youth with cerebral palsy (CP) often focus on activity-based strategies to promote functional mobility and participation in physical activity. The use of activity monitors validated for this populat ...

BioMed Central2019

Chemical machine learning with kernels: The key impact of loss functions

Volkan Cevher, Sandip De, Junhong Lin, Van Quang Nguyen

Machine learning promises to accelerate materials discovery by allowing computational efficient property predictions from a small number of reference calculations. As a result, the literature spent a considerable effort in designing representations that ca ...

2018

Pressure drop prediction in annular two-phase flow in macroscale tubes and channels

John Richard Thome, Andrea Cioncolini

A new prediction method for the frictional pressure drop in annular two-phase flow is presented. This new prediction method focuses on the aerodynamic interaction between the liquid film and the gas core in annular flows, and explicitly takes into account ...

Pergamon-Elsevier Science Ltd2017

Robust heart rate estimation using wrist-type photoplethysmographic signals during physical exercise: an approach based on adaptive filtering

Jean-Marc Vesin, Sibylle Fallet

Photoplethysmographic (PPG) signals are easily corrupted by motion artifacts when the subjects perform physical exercise. This paper introduces a two-step processing scheme to estimate heart rate (HR) from wrist-type PPG signals strongly corrupted by motio ...

Institute of Physics2017

How do Stability Corrections Perform in the Stable Boundary Layer Over Snow?

Michael Lehning, Wolf Hendrik Huwald, Sebastian Schlögl, Koichi Nishimura

We assess sensible heat-flux parametrizations in stable conditions over snow surfaces by testing and developing stability correction functions for two alpine and two polar test sites. Five turbulence datasets are analyzed with respect to, (a) the validity ...

2017