Results 31 to 40 of about 65,893 (254)
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
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
Higher Order Multivariate Fuzzy Approximation by basic Neural Network Operators [PDF]
Summary: Here are studied in terms of multivariate fuzzy high approximation to the multivariate unit basic sequences of multivariate fuzzy neural network operators. These operators are multivariate fuzzy analogs of earlier studied multivariate real ones. The produced results generalize earlier real ones into the fuzzy setting. Here the high order multi-
openaire +2 more sources
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane +4 more
wiley +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
GENERALIZED LOGISTIC NEURAL NETWORK APPROXIMATION OVER FINITE DIMENSION BANACH SPACES
The functions under approximation here have as a do main a finite dimensional Banach space with dimension N ∈ ℕ and are with values in R^N. Exploiting some topological properties of the above we are able to perform Neural Network multivariate ap ...
G. A. Anastassiou
doaj +1 more source
A Class of Logistic Functions for Approximating State-Inclusive Koopman Operators
An outstanding challenge in nonlinear systems theory is identification or learning of a given nonlinear system's Koopman operator directly from data or models.
arbabi +7 more
core +1 more source
Multivariate Fuzzy Perturbed Neural Network Operators Approximation
This article studies the determination of the rate of convergence to the unit of each of three newly introduced here multivariate fuzzy perturbed normalized neural network operators of one hidden layer. These are given through the multivariate fuzzy modulus of continuity of the involved multivariate fuzzy number valued function or its high order fuzzy ...
openaire +2 more sources
Using machine learning on a mega‐scale global dataset (n = 1,336,840) reveals a robust personality trait architecture beyond the Big Five. A Big Two model, broadly capturing social engagement and internal mentation, defines a geometric space that links personality to neurocognitive profiles.
Kaixiang Zhuang +7 more
wiley +1 more source
Network Uncertainty Informed Semantic Feature Selection for Visual SLAM
In order to facilitate long-term localization using a visual simultaneous localization and mapping (SLAM) algorithm, careful feature selection can help ensure that reference points persist over long durations and the runtime and storage complexity of the
Ganti, Pranav, Waslander, Steven L.
core +1 more source
Temporal and Cell‐Specific Regulation of Synaptic Homeostasis by the Chromatin Remodeler Chd1
Chd1, the Drosophila homologue of mammalian CHD2 ‐ a gene linked to autism, epilepsy, and intellectual disability, is required for synaptic homeostatic plasticity. Chd1 in glia is necessary for the rapid induction of synaptic homeostasis, whereas Chd1 in motoneurons, muscle, and glia is critical for long‐term maintenance.
Danielle T. Morency +19 more
wiley +1 more source

