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A novel source-filter stochastic model for voice production
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In: ISSN: 0892-1997 ; Journal of Voice ; https://hal-upec-upem.archives-ouvertes.fr/hal-03179837 ; Journal of Voice, Elsevier, 2021, In Press, pp.1-11. ⟨10.1016/j.jvoice.2020.11.015⟩ (2021)
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Writing At the Horizon: How Producing Imagined Narratives Affects Mood
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In: Senior Projects Fall 2021 (2021)
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Symbolic Model-based Design and Generation of Logical Scenarios for Autonomous Vehicles Validation
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In: 2021 IEEE Intelligent Vehicles Symposium (IV) ; https://hal.archives-ouvertes.fr/hal-03540190 ; 2021 IEEE Intelligent Vehicles Symposium (IV), Jul 2021, Nagoya, Japan. pp.215-222, ⟨10.1109/IV48863.2021.9575528⟩ (2021)
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Learning a weather dictionary of atmospheric patterns using Latent Dirichlet Allocation
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In: https://hal.archives-ouvertes.fr/hal-03258523 ; 2021 (2021)
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Neural Network Reconstruction of Late-Time Cosmology and Null Tests ...
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Drift in a Popular Metal Oxide Sensor Dataset Reveals Limitations for Gas Classification Benchmarks ...
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The Fundamental Limit Theorem of Countable Markov Chains
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In: Senior Honors Theses (2021)
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Combination of Time Series Analysis and Sentiment Analysis for Stock Market Forecasting
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In: Graduate Theses and Dissertations (2021)
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Free Energy: A User's Guide
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Abstract:
Over the last fifteen years, an ambitious explanatory framework has been proposed to unify explanations across biology and cognitive science. Active inference, whose most famous tenet is the free energy principle, has inspired excitement and confusion in equal measure. Here, we lay the ground for proper critical analysis of active inference, in three ways. First, we give simplified versions of its core mathematical models. Second, we outline the historical development of active inference and its relationship to other theoretical approaches. Third, we describe three different kinds of claim -- labelled mathematical, empirical and general -- routinely made by proponents of the framework, and suggest dialectical links between them. Overall, we aim to increase philosophical understanding of active inference so that it may be more readily evaluated. This is a manuscript draft of the Introduction to the Topical Collection "The Free Energy Principle: From Biology to Cognition", forthcoming in Biology & Philosophy.
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Keyword:
Biology; Cognitive Neuroscience; Decision Theory; Explanation; Models and Idealization; Probability/Statistics
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URL: http://philsci-archive.pitt.edu/19961/ http://philsci-archive.pitt.edu/19961/1/Free_Energy_A_Users_Guide.pdf
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Information flow, artificial phonology and typology
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In: Proceedings of the Society for Computation in Linguistics (2021)
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Heaps' law and Heaps functions in tagged texts: Evidences of their linguistic relevance ...
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Predictive Validity of Standards-based and Curriculum-embedded Assessments for Predicting Readiness at Kindergarten Entry
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In: Graduate Theses and Dissertations (2020)
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Monolingual and bilingual language networks in healthy subjects using functional MRI and graph theory ...
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The brevity law as a scaling law, and a possible origin of Zipf's law for word frequencies ...
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Multilabel text classification of public procurements using deep learning intent detection ; Textklassificering av offentliga upphandlingar med djupa artificiella neuronnät och avsåtsdetektering
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LSTM vs Random Forest for Binary Classification of Insurance Related Text ; LSTM vs Random Forest för binär klassificering av försäkringsrelaterad text
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The flow of ideologies between a political figure and a militant community: a CMC corpora analysis
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In: 6th Conference on Computer-Mediated Communication (CMC) and Social Media Corpora ; https://hal.archives-ouvertes.fr/hal-01872152 ; 6th Conference on Computer-Mediated Communication (CMC) and Social Media Corpora, Sep 2018, Anvers, Belgium (2018)
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Telling apart Felidae and Ursidae from the distribution of nucleotides in mitochondrial DNA ...
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