Results 161 to 170 of about 962,663 (328)

Multitarget Generate Electrolyte Additive for Lithium Metal Batteries

open access: yesAdvanced Materials, EarlyView.
This study presents a deep learning‐assisted generative model for electrolyte additives in lithium metal batteries (LMBs). The approach overcomes data scarcity by proposing the molecular categorization method and achieves 100% generative efficiency.
Xiangyang Liu   +12 more
wiley   +1 more source

Multi-Rules Mining Algorithm for Combinatorially Exploded Decision Trees With Modified Aitchison-Aitken Function-Based Bayesian Optimization

open access: yesIEEE Open Journal of the Computer Society
Decision trees offer the benefit of easy interpretation because they allow the classification of input data based on if–then rules. However, as decision trees are constructed by an algorithm that achieves clear classification with minimum ...
Yuto Omae, Masaya Mori, Yohei Kakimoto
doaj   +1 more source

Decision trees to evaluate the risk of developing multiple sclerosis. [PDF]

open access: yesFront Neuroinform, 2023
Pasella M   +9 more
europepmc   +1 more source

Sparse Projection Oblique Randomer Forests

open access: yes, 2019
Decision forests, including Random Forests and Gradient Boosting Trees, have recently demonstrated state-of-the-art performance in a variety of machine learning settings.
Browne, James   +10 more
core  

Designing an Anionic Layer in Low‐Concentration Electrolytes to Promote In‐Plane Ion Diffusion for Dendrite‐Free Zinc‐Ion Batteries

open access: yesAdvanced Materials, EarlyView.
An optimization model for zinc anodes centered on anion traction in a low‐concentration electrolyte system is proposed. The fluoride‐ion enriched interfacial layer on the zinc anode surface enhances the concentration of Zn2+ in a lateral direction through electrostatic forces, thereby facilitating horizontal zinc plating.
Yiyang Zhang   +9 more
wiley   +1 more source

Optimizing Interpretable Decision Tree Policies for Reinforcement Learning [PDF]

open access: yesarXiv
Reinforcement learning techniques leveraging deep learning have made tremendous progress in recent years. However, the complexity of neural networks prevents practitioners from understanding their behavior. Decision trees have gained increased attention in supervised learning for their inherent interpretability, enabling modelers to understand the ...
arxiv  

Spin Engineering of Dual‐Atom Site Catalysts for Efficient Electrochemical Energy Conversion

open access: yesAdvanced Materials, EarlyView.
This review highlights recent progress in spin engineering of dual‐atom site catalysts (DASCs), emphasizing how spin‐related properties enhance electrocatalytic activity, selectivity, and stability. It summarizes cutting‐edge developments in dual‐atom catalysis, discusses the underlying spin‐catalysis mechanisms and structure–performance relationships,
Dongping Xue   +5 more
wiley   +1 more source

Zero-Shot Decision Tree Construction via Large Language Models [PDF]

open access: yesarXiv
This paper introduces a novel algorithm for constructing decision trees using large language models (LLMs) in a zero-shot manner based on Classification and Regression Trees (CART) principles. Traditional decision tree induction methods rely heavily on labeled data to recursively partition data using criteria such as information gain or the Gini index.
arxiv  

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