[HTML][HTML] 2.0-MOOSE: Enabling massively parallel multiphysics simulation
The last 2 years have been a period of unprecedented growth for the MOOSE community
and the software itself. The number of monthly visitors to the website has grown from just …
and the software itself. The number of monthly visitors to the website has grown from just …
Computationally efficient multiscale neural networks applied to fluid flow in complex 3D porous media
The permeability of complex porous materials is of interest to many engineering disciplines.
This quantity can be obtained via direct flow simulation, which provides the most accurate …
This quantity can be obtained via direct flow simulation, which provides the most accurate …
Remapping in a recurrent neural network model of navigation and context inference
IIC Low, LM Giocomo, AH Williams - Elife, 2023 - elifesciences.org
Neurons in navigational brain regions provide information about position, orientation, and
speed relative to environmental landmarks. These cells also change their firing patterns …
speed relative to environmental landmarks. These cells also change their firing patterns …
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 …
when reconstructing accelerated MRI data. Methods Scan‐specific artifact reduction in k …
Current directions in combining simulation-based macromolecular modeling approaches with deep learning
VK Mulligan - Expert Opinion on Drug Discovery, 2021 - Taylor & Francis
Introduction: Structure-guided drug discovery relies on accurate computational methods for
modeling macromolecules. Simulations provide means of predicting macromolecular folds …
modeling macromolecules. Simulations provide means of predicting macromolecular folds …
Convergence of SGD with momentum in the nonconvex case: A novel time window-based analysis
We propose a novel time window-based analysis technique to investigate the convergence
behavior of the stochastic gradient descent method with momentum (SGDM) in nonconvex …
behavior of the stochastic gradient descent method with momentum (SGDM) in nonconvex …
Miffi: Improving the accuracy of CNN-based cryo-EM micrograph filtering with fine-tuning and Fourier space information
Efficient and high-accuracy filtering of cryo-electron microscopy (cryo-EM) micrographs is an
emerging challenge with the growing speed of data collection and sizes of datasets …
emerging challenge with the growing speed of data collection and sizes of datasets …
ArtiDock: fast and accurate machine learning approach to protein-ligand docking based on multimodal data augmentation
T Voitsitskyi, S Yesylevskyy, V Bdzhola, R Stratiichuk… - bioRxiv, 2024 - biorxiv.org
We present ArtiDock-the deep learning technique for predicting ligand poses in the protein
binding pockets (aka" AI docking"), which is based on augmenting inherently limited training …
binding pockets (aka" AI docking"), which is based on augmenting inherently limited training …
Verfahrensentwicklung für Schaltzeitprognosen an verkehrsabhängigen Lichtsignalanlagen mit Hilfe maschinellen Lernens
LE Schneegans - 2024 - kobra.uni-kassel.de
Im urbanen Raum, insbesondere vor signalisierten Knotenpunkten, entstehen die meisten
Emissionen des Straßenverkehrs. Eine Möglichkeit, um diese Emissionen zu senken, sind …
Emissionen des Straßenverkehrs. Eine Möglichkeit, um diese Emissionen zu senken, sind …
[PDF][PDF] UAV-based Anomaly Detection via a novel Spatial-Temporal Transformer for Precision Agriculture
H Cheng, H Li, J Lian - 2024 - cad-journal.net
Low altitude security has gained widespread concern for its applications, eg, cropland
monitoring. In this work, an Internet of Drones architecture was firstly presented for low …
monitoring. In this work, an Internet of Drones architecture was firstly presented for low …