Machine learning accelerated descriptor design for catalyst discovery in CO2 to methanol conversion by Prajwal Pisal, Ondřej Krejčí, Patrick Rinke

“…However, obtaining high methanol yields and ensuring the stability of heterocatalysts remain significant challenges. Herein, we present a sophisticated computational framework to accelerate the discovery of thermal heterogeneous catalysts, using machine-learned force fields. …”
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Nonlinear Volatility Risk Prediction Algorithm of Financial Data Based on Improved Deep Learning by Wangsong Xie

“…With the gradual integration of global economy and finance, the financial market presents many complex financial phenomena. To increase the prediction accuracy of financial data, a new nonlinear volatility risk prediction algorithm is proposed based on the improved deep learning algorithm. …”
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A non-asymptotic analysis of adaptive TD(λ) learning in wireless sensor networks by Bing Li, Tao Li, Muhua Liu, Junlong Zhu, Mingchuan Zhang, Qingtao Wu

“…(identically and independently distributed) noise in reinforcement learning. Moreover, we also present non-asymptotic analysis of ADTD( λ ) with both constant and diminishing step-sizes. …”
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Strategies for Using Assistive Technology to Overcome Students with Learning Disabilities and Barriers in Elementary School by Yesinta Dewi Aprilia, Beti Istanti Suwandayani, Kuncahyono

“… The present study identifies the implementation of assistive technology in students with learning disabilities and strategies for using assistive technology to overcome learning barriers. …”
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A tutorial review of policy iteration methods in reinforcement learning for nonlinear optimal control by Yujia Wang, Xinji Zhu, Zhe Wu

“…Reinforcement learning (RL) has been a powerful framework for designing optimal controllers for nonlinear systems. …”
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From Backtracking To Deep Learning: A Survey On Methods For Solving Constraint Satisfaction Problems by Fatima AIT HATRIT, Kamal AMROUN

“…To address this, extensive research has been conducted, leading to the development of effective techniques and algorithms for different types of CSPs, ranging from exhaustive search methods, which explore the entire search space, to modern techniques that use deep learning to learn how to solve CSPs. This paper represents a descriptive and synthetic overview of various CSPs solving methods, organized by approach: systematic search methods, inference and filtering methods, structural decomposition methods, local search-based methods, and deep learning-based methods. …”
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Reservoir Computing for Few-Mode Fiber Channel OSNR Monitoring in Deep Learning Frameworks by Jianjun Li, Tianfeng Zhao, Baojian Wu, Kun Qiu, Feng Wen

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DPmoire: a tool for constructing accurate machine learning force fields in moiré systems by Jiaxuan Liu, Zhong Fang, Hongming Weng, Quansheng Wu

“…To address this challenge, We introduce a robust methodology for the construction of machine learning potentials specifically tailored for moiré structures and present an open-source software package DPmoire designed to facilitate this process. …”
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An Interpretable Deep Learning-Based Feature Reduction in Video-Based Human Activity Recognition by Micheal Dutt, Morten Goodwin, Christian W. Omlin

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A new paradigm to study social and physical affordances as model-based reinforcement learning by Augustin Chartouny, Keivan Amini, Mehdi Khamassi, Benoît Girard

“…This new task is solved in simulation using a modular architecture and reinforcement learning.…”
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MoCoUTRL: a momentum contrastive framework for unsupervised text representation learning by Ao Zou, Wenning Hao, Dawei Jin, Gang Chen, Feiyan Sun

“…This paper presents MoCoUTRL: a Momentum Contrastive Framework for Unsupervised Text Representation Learning. …”
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Are AI weather models learning atmospheric physics? A sensitivity analysis of cyclone Xynthia by Jorge Baño-Medina, Agniv Sengupta, James D. Doyle, Carolyn A. Reynolds, Duncan Watson-Parris, Luca Delle Monache

“…This demonstrates the ability of the AI weather model to learn physically meaningful spatio-temporal links between atmospheric processes. …”
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Application of Faster R-CNN Deep Learning Method for Rice Plant Disease Detection by Halim Pujiono, Anik Vega Vitianingsih, Slamet Kacung, Anastasia Lidya Maukar, Seftin Fitri Ana Wati

“…Crop failure caused by rice plant diseases present a critical challenge for farmers.  Early diagnosis is crucial for preventing and managing rice diseases, as it facilitates more effective preventive measures, reduces yield losses, and boosts overall agricultural production. …”
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A Review of Vehicle Accident Detection and Notification Systems Based on Machine Learning Techniques by Duaa Hadi Nassar, Jamal Mustafa Al-Tuwaijari

“…The main purpose of this review article was to identify and collect all the studies that have been done previously to detect roads traffics based on using machine learning techniques particularly deep learning. This paper will present all the methods that have been used and the experimental results of these studies and the research gabs they contain. …”
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Local-non-local complementary learning network for 3D point cloud analysis by Ning Ye, Kaihao Feng, Sen Lin

“…However, the unstructured and disordered nature of point clouds presents significant challenges for feature extraction. …”
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Aplicación de Deep Learning al aprendizaje de modelos en robótica cognitiva by Ariel Rodríguez-Jiménez, Esteban Arias-Méndez, Francisco Bellas-Bouza, Jose Becerra-Permuy

“…Los entrenamientos experimentados son: Online Deep Learning, Online Deep Learning con memoria y Online Mini-Batch Deep Learning con memoria.…”
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T‐SNERF: A novel high accuracy machine learning approach for Intrusion Detection Systems by Mohamed Hammad, Nabil Hewahi, Wael Elmedany

“…Abstract In the last few decades, Intrusion Detection System (IDS), in particular, machine learning‐based anomaly detection, has gained importance over Signature Detection Systems (SDSs) in the novel attacks detection. …”
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An investigation of learning strategies & personality traits among proficient & less proficient ESL learners by Christine Shobana Arthur, Lee Luan Ng

“…The outcome of the present study would be useful to assist language instructors in helping less proficIent ESL learners in undergoing a more effective and successful second language leaming experience and enlighten proficient ESL learners about their preference in language learning strategies. …”
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EXPLORING STUDENT ALGEBRAIC THINKING IN SOLVING MATH PROBLEMS IN TERMS OF KOLB'S LEARNING STYLE by Aisya Rosida, Masduki Masduki

“…The finding also showed the CE stage learning style tends to use their experience about the prior knowledge had learned to solve the problem. …”
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Forming Critical Thinking: The Role of Students’ Epistemic Beliefs and Styles of Learning in Russian Universities by Kseniya V. Tarasova, Daniil P. Talov, Irina A. Shcheglova, Taras V. Pashchenko, Anastasiia Yu. Beliaeva

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