• Suche: "Learning and adaptive systems in artificial intelligence"

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1

A LoRA-Based Approach to Fine-Tuning LLMs for Educational Guidance in Resource-Constrained Settings
Hosen, Md Millat

Computer Science - Artif... 68T05 (Learning and adap...
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2

Artificial to Spiking Neural Networks Conversion with Calibration in Scientific Machine Learning: Artificial to spiking neural networks conversion with calibration in scientific machine learning
Qian Zhang ; Chenxi Wu ; Adar Kahana ; et al.
SIAM Journal on Scientific Computing. 47:C559-C577

scientific machine learn... PINN Learning and adaptive sy... Artificial neural networ... spiking neural network
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3

CoCoGen: Physically Consistent and Conditioned Score-Based Generative Models for Forward and Inverse Problems: CoCoGen: physically consistent and conditioned score-based generative models for forward and inverse problems
Christian Jacobsen ; Yilin Zhuang ; Karthik Duraisamy
SIAM Journal on Scientific Computing. 47:C399-C425

diffusion models FOS: Computer and inform... Inverse problems for PDE... Computer Science - Machi... Partial differential equ... generative AI …
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4

Uncertainty-Penalized Direct Preference Optimization
Houliston, Sam ; Pace, Alizée ; Immer, Alexander ; et al.

Computer Science - Machi... Computer Science - Artif... Statistics - Machine Lea... Learning and adaptive sy...
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5

Research on signal recognition method of acoustic beacon for underwater acoustic active and passive positioning dynamics system based on machine learning
Xu, Jinjin
Journal of Combinatorial Mathematics and Combinatorial Computing. 124:159-171

Signal theory (character... machine learning signal recognition Learning and adaptive sy... underwater acoustic acti... acoustic beacon
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6

DeepONet Based Preconditioning Strategies for Solving Parametric Linear Systems of Equations: DeepONet based preconditioning strategies for solving parametric linear systems of equations
Alena Kopaničáková ; George Em Karniadakis
SIAM Journal on Scientific Computing. 47:C151-C181

Large-scale problems in... Iterative numerical meth... operator learning Multigrid methods domain decomposition for... preconditioning …
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7

Limits of Learning Dynamical Systems: Limits of learning dynamical systems
Tyrus Berry ; Suddhasattwa Das
SIAM Review. 67:107-137

iterative forecast Learning and adaptive sy... 37M99, 37N30, 37A20, 37D... Dynamical Systems (math.... reservoir computing direct forecast …
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8

Reinforcement Learning‐Based Prescribed Performance Formation Control for USVs With Collision Avoidance and Preserved Connectivity: Reinforcement learning-based prescribed performance formation control for USVs with collision avoidance and preserved connectivity
Gengqi Li ; Wei Wang ; Liang Cao
International Journal of Robust and Nonlinear Control. 35:2996-3012

reinforcement learning optimal formation contro... unmanned surface vehicle... Learning and adaptive sy... preserved connectivity Automated systems (robot... …
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9

Prescribed‐Time Optimal Formation Synchronous Tracking Control of UAV‐Ugvs Based on Reinforcement Learning: Prescribed-time optimal formation synchronous tracking control of UAV-UGVs based on reinforcement learning
Shi‐Xun Xiong ; Guo‐Ping Jiang ; Yun‐Xia Zhu ; et al.
International Journal of Robust and Nonlinear Control. 35:2437-2450

optimal control reinforcement learning Learning and adaptive sy... Automated systems (robot... Existence theories for o... UAV-UGV formation …
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10

Automobile Insurance Fraud Detection Based on PSO-XGBoost Model and Interpretable Machine Learning Method: Automobile insurance fraud detection based on PSO-XGBoost model and interpretable machine learning method
Ding, Ning ; Ruan, Xiao ; Wang, Hao ; et al.
Insurance: Mathematics and Economics. 120:51-60

fraud detection automobile insurance SHAP Actuarial mathematics Learning and adaptive sy... PSO-XGBoost
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11

Adaptive Interface-PINNs (AdaI-PINNs): An Efficient Physics-Informed Neural Networks Framework for Interface Problems: Adaptive interface-PINNs (AdaI-PINNs): an efficient physics-informed neural networks framework for interface problems
Roy, Sumanta ; Annavarapu, Chandrasekhar ; Roy, Pratanu ; et al.
Communications in Computational Physics. 37:603-622

FOS: Computer and inform... I-PINNs Computer Science - Machi... physics-informed machine... Learning and adaptive sy... interface problems …
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12

Learning large-scale industrial physics simulations
Casenave, Fabien
European Mathematical Society Magazine. :5-13

Learning and adaptive sy... FOS: Mathematics Mathematics - Numerical... Numerical Analysis (math... General theory of mathem...
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13

How Much Data Is Sufficient to Learn High-Performing Algorithms?: How much data is sufficient to learn high-performing algorithms?
Maria-Florina Balcan ; Dan Deblasio ; Travis Dick ; et al.
Journal of the ACM. 71:1-58

0301 basic medicine data-driven algorithm de... 0303 health sciences 03 medical and health sc... machine learning computational biology …
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14

A Bayesian Approach for Learning Bayesian Network Structures: A Bayesian approach for learning Bayesian network structures
Zareifard, Hamid ; Tabar, Vahid Rezaei ; Javidian, Mohammad Ali ; et al.
Lobachevskii Journal of Mathematics. 45:4434-4447

Bayesian network directed acyclic graphs structure learning Estimation in multivaria... Bayesian inference Gibbs sampler …
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15

Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution: Auto-weighted Bayesian physics-informed neural networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution
Sarah Perez ; Philippe Poncet
Computational Geosciences. 28:1175-1215

FOS: Computer and inform... Computer Science - Machi... Bayesian physics-informe... uncertainty quantificati... Learning and adaptive sy... Computer Science - Neura... …
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16

New Douglas-Rashford Splitting Algorithms for Generalized DC Programming with Applications in Machine Learning: New Douglas-Rashford splitting algorithms for generalized DC programming with applications in machine learning
Yonghong Yao ; Lateef O. Jolaoso ; Yekini Shehu ; et al.
Journal of Scientific Computing. 103

machine learning Numerical mathematical p... DC programming Nonlinear programming Optimization and Control... nonconvex optimization …
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17

Self‐triggered control for linear systems based on hierarchical reinforcement learning: Self-triggered control for linear systems based on hierarchical reinforcement learning
Wei Chen ; Haiying Wan ; Xiaoli Luan ; et al.
International Journal of Robust and Nonlinear Control. 34:9112-9129

Hierarchical systems 0209 industrial biotechn... self-triggered control Linear systems in contro... model-free Learning and adaptive sy... …
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18

A multi-aggregator graph neural network for backbone exaction of fracture networks
Zheng, Tianji ; Sun, Chengcheng ; Zhang, Jian ; et al.
Computational Geosciences. 28:537-549

inductive learning Computational methods fo... backbone extraction Learning and adaptive sy... graph neural network discrete fracture networ...
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19

Impact of thermal radiations and viscous dissipation during the boundary layer non‐Newtonian fluid flow past a slender needle: Probed by machine learning: Impact of thermal radiations and viscous dissipation during the boundary layer non-Newtonian fluid flow past a slender needle: probed by machine learning
Hongxing Yao ; Asad Ullah ; null Ikramullah ; et al.
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik. 105

similarity transform Non-Newtonian fluids Learning and adaptive sy... Levenberg-Marquardt algo... Joule heating Magnetohydrodynamics and... …
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20

Random features and polynomial rules
Fabian Aguirre-Lopez ; Silvio Franz ; Mauro Pastore
SciPost Physics, Vol 18, Iss 1, p 039 (2025)

FOS: Computer and inform... Computer Science - Machi... Physics QC1-999 Learning and adaptive sy... FOS: Physical sciences …
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