Results 181 to 190 of about 45,458 (300)

Adaptive Riemannian optimization for multi-scale diffeomorphic matching. [PDF]

Nat Commun
Jena R, Chaudhari P, Gee JC.
europepmc   +1 more source

Methodological Approach for Particle Transport: Analyzing Influential Factors and Comparing Simulation Software

Chemie Ingenieur Technik, EarlyView.
This study determines the dust filtration behavior of venting tubes in automotive headlights. Numerical simulations using Meshfree and STAR‐CCM+ and suitable experiments were conducted to analyze the airflow field, the particle transport, and the filtration efficiency.
Cornelia Müssig, Alexander Kabat vel Job, Stephan Knorr, Henning Meyer, Daniel Wiest   +4 more
wiley   +1 more source

GeoRescue: A Geometric LiDAR Point Cloud Registration Framework for Resource-Constrained Edge Platforms. [PDF]

Sensors (Basel)
Sun Y, Shang Z, Yang M, Meng F, Mu M, Yan H.   +5 more
europepmc   +1 more source

A hidden Markov model and reinforcement learning‐based strategy for fault‐tolerant control

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study introduces a data‐driven control strategy integrating hidden Markov models (HMM) and reinforcement learning (RL) to achieve resilient, fault‐tolerant operation against persistent disturbances in nonlinear chemical processes. Called hidden Markov model and reinforcement learning (HMMRL), this strategy is evaluated in two case studies
Tamera Leitao, Debaprasad Dutta, Simant R. Upreti   +2 more
wiley   +1 more source

DupyliCate: mining, classifying, and characterizing gene duplications. [PDF]

Sci Rep
Natarajan S, Pucker B.
europepmc   +1 more source

Harnessing machine learning and optimization for informed chemical engineering decisions: A styrene reactor analysis

The Canadian Journal of Chemical Engineering, EarlyView.
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin, Clémence Fauteux‐Lefebvre, Jules Thibault   +2 more
wiley   +1 more source

BABAPPAlign: a multiple sequence alignment engine with a learned residue-level scoring function. [PDF]

Bioinformatics
Sinha K.
europepmc   +1 more source

Stochastic Gradient Descent in High Dimensions for Multi‐Spiked Tensor PCA

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We study the high‐dimensional dynamics of online stochastic gradient descent (SGD) for the multi‐spiked tensor model. This multi‐index model arises from the tensor principal component analysis (PCA) problem with multiple spikes, where the goal is to estimate the unknown signal vectors within the N$N$‐dimensional unit sphere through maximum ...
Gérard Ben Arous, Cédric Gerbelot, Vanessa Piccolo   +2 more
wiley   +1 more source

slideimp: efficient imputation of DNA methylation data. [PDF]

Bioinformatics
Pham H, Lombroso AP, Cevik EC, Taylor HS, O'Donnell KJ.   +4 more
europepmc   +1 more source

Quenching the Hubbard Model: Comparison of Nonequilibrium Green's Function Methods

Contributions to Plasma Physics, EarlyView.
ABSTRACT We benchmark nonequilibrium Green's function (NEGF) approaches for interaction quenches in the half‐filled Fermi–Hubbard model in one and two dimensions. We compare fully self‐consistent two‐time Kadanoff–Baym equations (KBE), the generalized Kadanoff–Baym ansatz (GKBA), and the recently developed NEGF‐based quantum fluctuations approach (NEGF‐
Jan‐Philip Joost, Christopher Makait, Alexander Osterkorn, Erik Schroedter   +3 more
wiley   +1 more source