Enhanced hierarchical attention networks for predictive interactome analysis of LncRNA and CircRNA in oral herpes virus by Pradeep Kumar Yadalam, Carlos M. Ardila

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Encoding Longer-Term Contextual Information with Predictive Coding and Ego-Motion by Junpei Zhong, Angelo Cangelosi, Tetsuya Ogata, Xinzheng Zhang

“…It integrates the perception and action in the predictive coding framework. Moreover, in this neural network model, there are different temporal scales of predictions existing on different levels of the hierarchical predictive coding architecture, which defines the temporal memories in recording the events occurring. …”
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Recurrent predictive coding models for associative memory employing covariance learning. by Mufeng Tang, Tommaso Salvatori, Beren Millidge, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz

“…We further show that our models can be combined with hierarchical predictive coding networks to model the hippocampo-neocortical interactions. …”
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A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters by Muhammad Asif, Maaz Bin Ahmad, Imtiaz A. Taj, Muhammad Tahir

“…The exploitation of the RDO technique contributes significantly to increase the computational complexity of the coding process. In this paper, a generalized multi-layer framework is presented, which provides a hierarchical optimized way to select MB prediction parameters. …”
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Hybrid Lossless Image Compression Using Wavelet Trans-form and Hierarchical non Linear Prediction by Rana Talib Al-Timimi

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Energy optimization induces predictive-coding properties in a multi-compartment spiking neural network model. by Mingfang Zhang, Raluca Chitic, Sander M Bohté

“…Predictive coding is a prominent theoretical framework for understanding hierarchical sensory processing in the brain, yet how it could be implemented in networks of cortical neurons is still unclear. …”
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Neurocomputational Mechanisms of Sense of Agency: Literature Review for Integrating Predictive Coding and Adaptive Control in Human–Machine Interfaces by Anirban Dutta

“…Methods: I reviewed the foundational and contemporary literature on predictive coding, Kalman filtering, the Linear–Quadratic–Gaussian (LQG) control framework, and active inference. …”
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Dissociated neuronal cultures as model systems for self-organized prediction by Amit Yaron, Zhuo Zhang, Dai Akita, Tomoyo Isoguchi Shiramatsu, Zenas C. Chao, Hirokazu Takahashi, Hirokazu Takahashi

“…This review synthesizes and critically examines research demonstrating their fundamental computational abilities, including predictive coding, adaptive learning, goal-directed behavior, and deviance detection. …”
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MEN: leveraging explainable multimodal encoding network for precision prediction of CYP450 inhibitors by Abena Achiaa Atwereboannah, Wei-Ping Wu, Mugahed A. Al-antari, Sophyani B. Yussif, Chukwuebuka J. Ejiyi, Edwin K. Tenagyei, Grace-Mercure B. Kissanga, Gyarteng S. A. Emmanuel, Yeong Hyeon Gu, Emmanuel Ahene

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Efficacy and Autopoiesis of the System of Science, Education, Law and Politics by Ksenija Grubišić

“…The paper examines whether and in what way the interpretation of the efficacy of the legal system by means of the reduced principle of imputation differs, or is insufficient, in relation to the reduction of complexity of the legal system by means of codes and operations that make it autopoietic. …”
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GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity by Junwei Luo, Ziguang Zhu, Zhenhan Xu, Chuanle Xiao, Jingjing Wei, Jiquan Shen

“…Finally, the obtained drug and protein feature vectors are combined to predict DTA through the fully connected layer. The source code can be downloaded from https://github.com/zhuziguang/GS-DTA . …”
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Network level spatial temporal traffic forecasting with Hierarchical-Attention-LSTM by Tianya Zhang

“…The efficiency of the designed hierarchical LSTM is analyzed by ablation study, demonstrating that the attention-pooling mechanism in both cell and hidden states not only provides higher prediction accuracy but also effectively forecasts unusual congestion patterns. …”
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A Novel Similarity Score for Link Prediction Approach Using Financial Transaction Networks and Firms’ Attribute by Aparajita Bose, Byunghoon Kim

“…Existing studies often overlook important features such as the direction of transactions between firms, the hierarchical nature of transaction networks, and the significance of node attributes, thereby hindering accurate link prediction. …”
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Hierarchical classification of scientific articles using deep learning (using the UDC hierarchy as an example) by Valentin Y. Mamedov, Danil A. Kovalevsky, Dmitry A. Morozov, Stepan S. Stolyarov, Sergey S. Ospichev

“…Furthermore, blind expert evaluation revealed that discrepancies between reference and predicted labels often stem from errors in the original UDC code assignments by article authors. …”
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Microgrid stability: A comprehensive review of challenges, trends, and emerging solutions by Nima Khosravi, Doğan Çelik, Hassan Bevrani, Salwa Echalih

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Development of a work systems stress questionnaire to predict job burnout: A mixed methods study based on a macroergonomics approach by Rahman Zare, Reza Kazemi, Alireza Choobineh, Rosanna Cousins, Andrew Smith, Hamidreza Mokarami

“…Hierarchical linear regression modelling of the data indicated that Task Significance, Job Demands, Work-Life Conflict, and Work Schedule predicted Emotional Exhaustion, and altogether explained 58 % variance. …”
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An automatic ICD coding method for clinical records based on deep neural network by Yichao DU, Tong XU, Jianhui MA, Enhong CHEN, Yi ZHENG, Tongzhu LIU, Guixian TONG

“…With the increase in the number of the international classification of diseases (ICD) codes,the difficulty and cost of manual coding based on clinical records have greatly increased,and automatic ICD coding technology has attracted widespread attention.A multi-scale residual graph convolution network automatic ICD coding technology was proposed.This technology uses a multi-scale residual network to capture text patterns of different lengths of clinical text and extracts the hierarchical relationship between labels based on the graph convolutional neural network to enhance the ability of automatic coding.The experimental results on the real medical data set MIMIC-III show that the P@k and Micro-F1 of this method are 72.2% and 53.9%,respectively,which significantly improves the prediction performance.…”
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Multi-Scale Contextual Coding for Human-Machine Vision of Volumetric Medical Images by Jietao Chen, Weijie Chen, Qianjian Xing, Feng Yu

“…To reduce the compression bit cost, we create a Multi-Dimensional Entropy Model that integrates inter-slice latent context with spatial-channel context and hierarchical hypercontext. Experimental results demonstrate that our framework obtains an average 9% BD-Rate reduction over the Versatile Video Coding (VVC) anchor on MRNet datasets, while achieving superior recognition performance for downstream segmentation and classification tasks than inputting reconstructed lossy images.…”
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Enhanced clustering techniques for lithofacies and electrofacies identification in post-salt carbonate and siliciclastic reservoirs: a case study from the campos basin, Brazil by Abel Carrasquilla, Herson Rocha

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Assimilation of the total electron content obtained from GNSS to a model of the ionosphere using a hierarchical Bayesian network by Tang Jun, Hu Jiacheng, Zhang Wei, Fan Cihang, Zhou Qiangbo

“…Additionally, the HBN-based PPP method demonstrates slightly improved GNSS positioning accuracy compared to CODE-based PPP, with a reduction in RMSE observed under both geomagnetically disturbed and quiet conditions. …”
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