Results 61 to 70 of about 129,562 (262)
Sequential Gaussian Processes for Online Learning of Nonstationary Functions
, 2019 Many machine learning problems can be framed in the context of estimating functions, and often these are time-dependent functions that are estimated in real-time as observations arrive.
Dumitrascu, Bianca +3 more
core +1 more source
Optuna: Finding the optimal hyperparameters
, 2023 Application of Optuna to find the optimal hyperparameters for transfer learning or fine tuning the pre-trained models This code was used to find best hyperparameters to classify MS and Normal cases using SLO images. However it can be used in any other application.
Aghababaei Ali +2 more
openaire +1 more source
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
Advanced Functional Materials, EarlyView.An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source
A Genetic Algorithm Based Optimized Convolutional Neural Network for Face Recognition
International Journal of Applied Mathematics and Computer Science, 2023 Face recognition (FR) is one of the most active research areas in the field of computer vision. Convolutional neural networks (CNNs) have been extensively used in this field due to their good efficiency.
Karlupia Namrata +3 more
doaj +1 more source
Gaussian process based model predictive control : a thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Engineering, School of Engineering and Advanced Technology, Massey University, New Zealand [PDF]
, 2017 The performance of using Model Predictive Control (MPC) techniques is highly dependent on a model that is able to accurately represent the dynamical system. The datadriven modelling techniques are usually used as an alternative approach to obtain such
Cao, Gang
core
On the Design of LQR Kernels for Efficient Controller Learning
, 2017 Finding optimal feedback controllers for nonlinear dynamic systems from data is hard. Recently, Bayesian optimization (BO) has been proposed as a powerful framework for direct controller tuning from experimental trials. For selecting the next query point
Hennig, Philipp +3 more
core +1 more source
Advanced Functional Materials, EarlyView.We present a fully automated Bayesian optimization (BO) protocol for the parameterization of nonbonded interactions in coarse‐grain CG force fields (BACH). Using experimental thermophysical data, we apply the protocol to a broad range of liquids, spanning linear, branched, and unsaturated hydrocarbons, esters, triglycerides, and water.
Janak Prabhu +3 more
wiley +1 more source
COVIDNet: Implementing Parallel Architecture on Sound and Image for High Efficacy
Future Internet, 2021 The present work relates to the implementation of core parallel architecture in a deep learning algorithm. At present, deep learning technology forms the main interdisciplinary basis of healthcare, hospital hygiene, biological and medicine.
Manickam Murugappan +4 more
doaj +1 more source
An Experimental Evaluation of Bayesian Optimization on Bipedal Locomotion
, 2013 © 2014 IEEE.The design of gaits and corresponding control policies for bipedal walkers is a key challenge in robot locomotion. Even when a viable controller parametrization already exists, finding near-optimal parameters can be daunting.
Calandra, R +3 more
core +1 more source
Advanced Healthcare Materials, EarlyView.Antimicrobial peptide (AMP)‐loaded nanocarriers provide a multifunctional strategy to combat drug‐resistant Mycobacterium tuberculosis. By enhancing intracellular delivery, bypassing efflux pumps, and disrupting bacterial membranes, this platform restores phagolysosome fusion and macrophage function.
Christian S. Carnero Canales +11 more
wiley +1 more source