Speech Stream Composition Affects Statistical Learning: Behavioral and Neural Evidence by Ana Paula Soares, Dario Paiva, Alberto Lema, Diana R. Pereira, Ana Cláudia Rodrigues, Helena Mendes Oliveira

“…Here, we tested if SL is affected by the composition of the speech streams by expositing participants to auditory streams containing either four nonsense words presenting a transitional probability (TP) of 1 (unmixed high-TP condition), four nonsense words presenting TPs of 0.33 (unmixed low-TP condition) or two nonsense words presenting a TP of 1, and two of a TP of 0.33 (mixed condition); first under incidental (implicit), and, subsequently, under intentional (explicit) conditions to further ascertain how prior knowledge modulates the results. …”
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Stochastic Explicit Calibration Algorithm for Survival Models by Jeongho Park, Sangwook Kang, Gwangsu Kim

“…Although extensive research has focused on calibration in classification and regression tasks using deep neural networks, survival analysis remains relatively underexplored, resulting in the lack of improved calibration methods. …”
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I-NeRV: A Single-Network Implicit Neural Representation for Efficient Video Inpainting by Jie Ji, Shuxuan Fu, Jiaju Man

“…However, the limited size of the video embedding (e.g., <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>16</mn><mo>×</mo><mn>2</mn><mo>×</mo><mn>4</mn></mrow></semantics></math></inline-formula>) generated by the encoder restricts the available feature information for the decoder, which, in turn, constrains the model’s representational capacity and degrades inpainting performance. While implicit neural representations have shown promise for video inpainting, most of the existing research still revolves around image inpainting and does not fully account for the spatiotemporal continuity and relationships present in videos. …”
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Analysis of Four-Species Diffusive and Non-Diffusive Food Chains Using Artificial Neural Networking by Muhammad Shoaib Arif, Ateeq Ur Rehman, Asad Ejaz

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Motor-based prediction mediates implicit vocal imitation by Yuchunzi Wu, Zhili Han, Xing Tian

“…Motor-based predictions orchestrate sensorimotor interaction and memory-based operations to mediate implicit learning behaviour in a social context.…”
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NeuSD: Surface Completion With Multi-View Text-to-Image Diffusion by Savva Ignatyev, Daniil Selikhanovych, Oleg Voynov, Yiqun Wang, Peter Wonka, Stamatios Lefkimmiatis, Evgeny Burnaev

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Aquifer vulnerability assessment in data-scarce areas: a spatially explicit assessment by Changhyun Jun, Dongkyun Kim, Sayed M. Bateni, Meghdad Biyari, Ely Salwana, Farzaneh Sajedi Hosseini, Amir Mosavi, Hao-Ting Pai, Bahram Choubin

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LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology by Matthew Ho, Deaglan J. Bartlett, Nicolas Chartier, Carolina Cuesta-Lazaro, Simon Ding, Axel Lapel, Pablo Lemos, Christopher C. Lovell, T. Lucas Makinen, Chirag Modi, Viraj Pandya, Shivam Pandey, Lucia A. Perez, Benjamin Wandelt, Greg L. Bryan

“…This paper presents the Learning the Universe Implicit Likelihood Inference (LtU-ILI) pipeline, a codebase for rapid, user-friendly, and cutting-edge machine learning (ML) inference in astrophysics and cosmology. …”
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From Code to Ratings: Converting Programming Data to Enhance Collaborative Filtering in Educational Online Judge Systems by Daniel M. Muepu, Yutaka Watanobe

“…This study introduces and compares three innovative approaches for recommending programming problems within an Online Judge system (OJ), tackling the challenge of deriving implicit ratings from user interactions without explicit user ratings. …”
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Ortho-NeRF: generating a true digital orthophoto map using the neural radiance field from unmanned aerial vehicle images by Shihan Chen, Qingsong Yan, Yingjie Qu, Wang Gao, Junxing Yang, Fei Deng

“…Hence, the need for further improvements in both mapping accuracy and automation is highlighted. In this paper, we present an approach for generating a TDOM based on a Neural Radiance Field (NeRF) without utilizing prior three-dimensional geometry information called an Ortho Neural Radiance Field (Ortho-NeRF). …”
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A Hybrid Method for Implicit Intention Inference Based on Punished-Weighted Na&#x00EF;ve Bayes by Zheng Gao, Shiqian Wu, Zhonghua Wan, Sos Agaian

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Explicit and explainable artificial intelligent model for prediction of CO2 molecular diffusion coefficient in heavy crude oils and bitumen by Saad Alatefi, Okorie Ekwe Agwu, Ahmad Alkouh

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Visualization and workload with implicit fNIRS-based BCI: toward a real-time memory prosthesis with fNIRS by Matthew Russell, Samuel Hincks, Liang Wang, Amin Babar, Zaiyi Chen, Zachary White, Robert J. K. Jacob

“…Functional Near-Infrared Spectroscopy (fNIRS) has proven in recent time to be a reliable workload-detection tool, usable in real-time implicit Brain-Computer Interfaces. But what can be done in terms of application of neural measurements of the prefrontal cortex beyond mental workload? …”
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Leveraging Neural Trojan Side-Channels for Output Exfiltration by Vincent Meyers, Michael Hefenbrock, Dennis Gnad, Mehdi Tahoori

“…Additionally, we explore countermeasures and discuss their implications for the design of secure neural network accelerators. To the best of our knowledge, this work is the first to present a passive output recovery attack on neural network accelerators, without explicit trigger mechanisms. …”
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Benchmarking Spiking Neural Network Learning Methods With Varying Locality by Jiaqi Lin, Sen Lu, Malyaban Bal, Abhronil Sengupta

“…Further, given the implicitly recurrent nature of SNNs, this research investigates the influence of the addition of explicit recurrence to SNNs. …”
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Neural correlates reveal separate stages of spontaneous face perception by Amanda K. Robinson, Greta Stuart, Sophia M. Shatek, Adrian Herbert, Jessica Taubert

“…While this illusion reveals the automaticity of face detection, it also presents a paradox: how does the brain process stimuli that are simultaneously faces and objects? …”
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SIGNETS: Neural Network Architectures for m-QAM Soft Demodulation by Aravind R. Voggu, Kanish R, Nishith Akula, Lohitaksh Maruvada, Takanori Shimizu, Madhav Rao

“…This paper presents a novel approach to Quadrature Amplitude Modulation (QAM) demodulation using neural networks, addressing the limitations of traditional demodulation techniques in complex channel conditions. …”
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Predefined-Time Antisynchronization of Two Different Chaotic Neural Networks by Lixiong Lin

“…The designed controller presents the practical advantage that the least upper bound for the settling time can be explicitly defined during the control design. …”
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Common neural recruitment across diverse sustained attention tasks. by Jessica A Grahn, Tom Manly

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Neural network distillation of orbital dependent density functional theory by Matija Medvidović, Jaylyn C. Umana, Iman Ahmadabadi, Domenico Di Sante, Johannes Flick, Angel Rubio

“…These goals are achieved by using a recently developed class of robust neural network models capable of modeling functionals, as opposed to functions, with explicitly enforced spatial symmetries. …”
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