Personalized learning path planning for higher education based on deep generative models and quantum machine learning: a multimodal learning analysis method integrating transformer, adversarial training and quantum state classification by Changzhi Sun, Shijie Huang, Banghui Sun, Shiwei Chu

Subjects: “…Learning path planning…”
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Students’ opinions about modern lecture: development path by Tatyana A. Astashova

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The AI revolution in micro-credentialing: personalized learning paths by Pooja Shanmughan, Jeena Joseph, Brinda Nair S., Anitha S. M., Anuja C. S., Jobin Jose

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Path-minimizing latent ODEs for improved extrapolation and inference by Matt L Sampson, Peter Melchior

“…By replacing the common variational penalty in latent space with an $\ell_2$ penalty on the path length of each system, the models learn data representations that can easily be distinguished from those of systems with different configurations. …”
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Dynamic Knowledge Path Learning for Few-Shot Learning by Jingzhu Li, Zhe Yin, Xu Yang, Jianbin Jiao, Ye Ding

“…Few-shot learning is a challenging task that aims to train a classifier with very limited training samples. …”
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System Logs Anomaly Detection. Are we on the right path? by Ramona-Georgiana Albert

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ONLINE SCHOOL: BIOGRAPHICAL RECONSTRUCTION OF AN ALTERNATIVE THE EDUCATIONAL PATH by Zoya V. Proshkova, Evgeniy D. Yeremenko

“…The study used a biographical method: the collection of autobiographical writings about the educational path and the educational experience gained in online schools. …”
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The Path and Trends in Information Science and Technology Curriculum Construction by XIONG Zhang, TANG Xiaolan

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Research on AGV Path Planning Based on Improved DQN Algorithm by Qian Xiao, Tengteng Pan, Kexin Wang, Shuoming Cui

“…To address these issues, in this paper, an adaptive path planning algorithm with an improved Deep Q Network algorithm called the B-PER DQN algorithm is proposed. …”
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ProvNavigator: shadow path guided attack investigation method by XI Hao, FAN Hao, YUAN Shenyang, ZHU Jinyu, CHEN Changhua, WAN Hai, ZHAO Xibin

“…In the attack investigation phase, nodes with dependency explosion were handled through “shadow path pairs,” and appropriate edges were selected to reconstruct the entire attack chain. …”
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Physics-Informed Graph Neural Networks for Attack Path Prediction by Marin François, Pierre-Emmanuel Arduin, Myriam Merad

“…While machine learning (ML) has proven effective in predicting the exploitation of individual vulnerabilities, its potential for full-path prediction remains largely untapped. This challenge stems from two key obstacles: the lack of adequate datasets for training the models and the dimensionality of the learning problem. …”
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The path to “Integral Protection”: The evolution and challenges of child protection in Brazil by Sidnei Priolo Filho, Luciana C. Assini-Meytin, Natalia Kerche Alvaides, Andreza Porto Lourenço, Renan Hoinski, Matheus Carrascoso, Ana Rebeca Benevides, Silvio José Benelli, Tiago Gagliano, Sabrina Mazo D'Affonseca

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Comparing the neural network with path analysis in fitting regression models by Fereshteh Aard, Ayyub Sheikhi

“…The results of the analysis showed that both models are over fitted and the RMSE train and test of neural network are less different from the path analysis. …”
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Rough-Terrain Path Planning Based on Deep Reinforcement Learning by Yufeng Yang, Zijie Zhang

“…For the problem of the low exploration efficiency of the ε-greedy strategy, a hybrid exploration strategy combining stochastic exploration and the A* algorithm is proposed, after which the agent is trained on rough terrain. The results show that the algorithm can efficiently plan energy-saving paths, converge quickly, and compared with the traditional A* algorithm and RRT algorithm, performs better under three-dimensional terrain and can choose paths more rationally.…”
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Healthcare personnel on the frontline of immunization: Barriers to vaccination and the path to full coverage by Saliha Büşra Aksu, Seda Özmen Sever, Beray Gelmez Taş, İlknur Demir, Güzin Zeren Öztürk

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Dynamic Path Planning of Unknown Environment Based on Deep Reinforcement Learning by Xiaoyun Lei, Zhian Zhang, Peifang Dong

“…In this paper, we apply double Q-network (DDQN) deep reinforcement learning proposed by DeepMind in 2016 to dynamic path planning of unknown environment. The reward and punishment function and the training method are designed for the instability of the training stage and the sparsity of the environment state space. …”
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Using a deep learning neural network to predict flight path by Oleksandr Bezsonov, Serhii Liashenko, Oleg Rudenko, Sofiia Rutska, Kateryna Vashchenko

“…The scientific novelty of the obtained results lies in the development and training of deep learning models specifically designed for predicting drone flight paths. …”
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An Enhanced Artificial Lemming Algorithm and Its Application in UAV Path Planning by Xuemei Zhu, Chaochuan Jia, Jiangdong Zhao, Chunyang Xia, Wei Peng, Ji Huang, Ling Li

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Career path prediction using XGBoost Model and students’ academic results by Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh

“…After that, the algorithm uses the training subset to build the classification model. …”
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Career path prediction using XGBoost Model and students’ academic results by Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh

“…After that, the algorithm uses the training subset to build the classification model. …”
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