Code program. حسب Honglei Pang (22693724)

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The HIL simulation data flowchart. حسب Honglei Pang (22693724)

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Steering system model. حسب Honglei Pang (22693724)

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Hyperparameter Configurations in PPO Training. حسب Honglei Pang (22693724)

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Main parameters of steering system. حسب Honglei Pang (22693724)

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Co-simulation architecture. حسب Honglei Pang (22693724)

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Overall framework diagram of the study. حسب Honglei Pang (22693724)

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Braking system model. حسب Honglei Pang (22693724)

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Vehicle parameters. حسب Honglei Pang (22693724)

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Locally sparse function-on-function regression حسب Mauro Bernardi (418110)

"…Herein, we consider the case where both the response and covariates are functions. …"

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... حسب Hector Torres (11708207)

On the improvement of reinforcement active learning with the involvement of cross entropy to address one-shot learning problem حسب Honglan Huang (341951)

"…With the involvement of cross-entropy in the loss function of Q-learning, an efficient policy to decide when and where to predict or query an instance is learned through the developed framework. …"

Task structure diagram. حسب Honglan Huang (341951)

Available functions in the phase-shifting package. حسب Raul Castañeda (13932971)

Available functions in the numerical propagation package. حسب Raul Castañeda (13932971)

Available functions in the phase reconstruction package. حسب Raul Castañeda (13932971)

“trend+var” algorithm. حسب Roman Olson (6577004)

State Preparation in Quantum Algorithms for Fragment-Based Quantum Chemistry حسب Ruhee D’Cunha (8921372)

"…The localized active space–unitary coupled cluster (LAS–UCC) algorithm iteratively loads a fragment-based multireference wave function onto a quantum computer. …"

Physics-Informed Bayesian Optimization for Conformational Ensemble Augmentation حسب Ivan A. Bespalov (21491561)

"…In this paper, we introduce a Bayesian optimization algorithm for conformational ensemble augmentation, that is, locating missing conformers in an existing ensemble, which employs Bayesian optimization with physics-informed torsion-potential-based kernel function and a novel acquisition function that prioritizes potential energy surface exploration for increased conformer diversity. …"

Physics-Informed Bayesian Optimization for Conformational Ensemble Augmentation حسب Ivan A. Bespalov (21491561)

"…In this paper, we introduce a Bayesian optimization algorithm for conformational ensemble augmentation, that is, locating missing conformers in an existing ensemble, which employs Bayesian optimization with physics-informed torsion-potential-based kernel function and a novel acquisition function that prioritizes potential energy surface exploration for increased conformer diversity. …"