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Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks

Publications associées (44)

ON THE RELATIONSHIP BETWEEN SPEECH-BASED BREATHING SIGNAL PREDICTION EVALUATION MEASURES AND BREATHING PARAMETERS ESTIMATION

Zohreh Mostaani, Venkata Srikanth Nallanthighal

The respiratory system is one of the major components of the speech production system. Any alteration in breathing can result in changes in speech. Specific breathing characteristics, such as breathing rate and tidal volume, can indicate a person's patholo ...
2021

On The Relationship Between Speech-Based Breathing Signal Prediction Evaluation Measures And Breathing Parameters Estimation

Mathew Magimai Doss, Zohreh Mostaani, Venkata Srikanth Nallanthighal

The respiratory system is one of the major components of the speech production system. Any alteration in breathing can result in changes in speech. Specific breathing characteristics, such as breathing rate and tidal volume, can indicate a person's patholo ...
IEEE2021

Scan-specific artifact reduction in k-space (SPARK) neural networks synergize with physics-based reconstruction to accelerate MRI

Purpose: To develop a scan-specific model that estimates and corrects k-space errors made when reconstructing accelerated MRI data. Methods: Scan-specific artifact reduction in k-space (SPARK) trains a convolutional-neural-network to estimate and correct k ...
WILEY2021

Biomechanical Ambulatory Assessment of 3D Knee Angle Using Novel Inertial Sensor-Based Technique

Kamiar Aminian, Lai Kuan Tham

Three-dimensional (3D) knee angle measurement is one of the key measures in human gait analysis. Inertial sensor capable of measuring joint motion under unconstrained conditions is a practical tool for clinical evaluation and rehabilitation. An inertial me ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Physics-informed machine learning for reduced-order modeling of nonlinear problems

Qian Wang, Jan Sickmann Hesthaven

A physics-informed machine learning framework is developed for the reduced-order modeling of parametrized steady-state partial differential equations (PDEs). During the offline stage, a reduced basis is extracted from a collection of high-fidelity solution ...
2020

Investigation of effective processes parameters on lead (II) adsorption from wastewater by biochar in mild air oxidation pyrolysis process

Mohsen Talebkeikhah, Farzaneh Talebkeikhah, Mohammad Torkashvand

This study evaluates and compares several machine learning methods on the effects of different parameters in lead adsorption capacity. pH, contact time, adsorbent dosage and initial lead concentration were considered as inputs and adsorption capacity was r ...
TAYLOR & FRANCIS LTD2020

Physico-chemical properties prediction of hydrochar in macroalgae Sargassum horneri hydrothermal carbonisation

Mohsen Talebkeikhah, Farzaneh Talebkeikhah

This study evaluates and compares several machine learning methods on the effects of different parameters in the hydrothermal carbonisation (HTC) process of macroalgae Sargassum horneri. Reaction temperature, residence time, biomass particle size, the amou ...
TAYLOR & FRANCIS LTD2019

Force Characterization Of Meso-Scale Haptic Devices

Jamie Paik, Sagar Dattatray Joshi, Frédéric Henri Vaskin Giraud

Recent advances with haptic devices have shown great potential in physically simulating contact with an object. In meso-scale (1 to 10 cm) haptic devices, although the actuation level can be controlled, their small form-factor makes it difficult to measure ...
2019

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