21 found
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  1.  19
    (1 other version)Perception of speech reflects optimal use of probabilistic speech cues.Meghan Clayards, Michael K. Tanenhaus, Richard N. Aslin & Robert A. Jacobs - 2008 - Cognition 108 (3):804-809.
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  2.  32
    Visual shape perception as Bayesian inference of 3D object-centered shape representations.Goker Erdogan & Robert A. Jacobs - 2017 - Psychological Review 124 (6):740-761.
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  3.  12
    Efficient data compression in perception and perceptual memory.Christopher J. Bates & Robert A. Jacobs - 2020 - Psychological Review 127 (5):891-917.
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  4.  20
    Learning abstract visual concepts via probabilistic program induction in a Language of Thought.Matthew C. Overlan, Robert A. Jacobs & Steven T. Piantadosi - 2017 - Cognition 168 (C):320-334.
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  5.  38
    An ideal observer analysis of visual working memory.Chris R. Sims, Robert A. Jacobs & David C. Knill - 2012 - Psychological Review 119 (4):807-830.
  6.  20
    A probabilistic clustering theory of the organization of visual short-term memory.A. Emin Orhan & Robert A. Jacobs - 2013 - Psychological Review 120 (2):297-328.
  7.  34
    Encoding Shape and Spatial Relations: The Role of Receptive Field Size in Coordinating Complementary Representations.Robert A. Jacobs & Stephen M. Kosslyn - 1994 - Cognitive Science 18 (3):361-386.
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  8.  30
    Melioration as rational choice: Sequential decision making in uncertain environments.Chris R. Sims, Hansjörg Neth, Robert A. Jacobs & Wayne D. Gray - 2013 - Psychological Review 120 (1):139-154.
  9.  36
    Transfer of object category knowledge across visual and haptic modalities: Experimental and computational studies.Ilker Yildirim & Robert A. Jacobs - 2013 - Cognition 126 (2):135-148.
  10. A Rational Analysis of the Acquisition of Multisensory Representations.Ilker Yildirim & Robert A. Jacobs - 2012 - Cognitive Science 36 (2):305-332.
    How do people learn multisensory, or amodal, representations, and what consequences do these representations have for perceptual performance? We address this question by performing a rational analysis of the problem of learning multisensory representations. This analysis makes use of a Bayesian nonparametric model that acquires latent multisensory features that optimally explain the unisensory features arising in individual sensory modalities. The model qualitatively accounts for several important aspects of multisensory perception: (a) it integrates information from multiple sensory sources in such a (...)
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  11.  11
    Implications of capacity-limited, generative models for human vision.Joseph Scott German & Robert A. Jacobs - 2023 - Behavioral and Brain Sciences 46:e391.
    Although discriminative deep neural networks are currently dominant in cognitive modeling, we suggest that capacity-limited, generative models are a promising avenue for future work. Generative models tend to learn both local and global features of stimuli and, when properly constrained, can learn componential representations and response biases found in people's behaviors.
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  12. Visual Learning in Multisensory Environments.Robert A. Jacobs & Ladan Shams - 2010 - Topics in Cognitive Science 2 (2):217-225.
    We study the claim that multisensory environments are useful for visual learning because nonvisual percepts can be processed to produce error signals that people can use to adapt their visual systems. This hypothesis is motivated by a Bayesian network framework. The framework is useful because it ties together three observations that have appeared in the literature: (a) signals from nonvisual modalities can “teach” the visual system; (b) signals from nonvisual modalities can facilitate learning in the visual system; and (c) visual (...)
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  13. Journal of The Cognitive Science Society.Robert L. Goldstone, John R. Anderson, Nick Chater, Andy Clark, Shimon Edelman, Kenneth Forbus, Dedre Gentner, Raymond W. Gibbs Jr, James Greeno & Robert A. Jacobs - 2004 - Cognitive Science 28 (3).
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  14. Does Stimulus Category Coherence Influence Visual Working Memory? A Rational Analysis.Ruoyang Hu & Robert A. Jacobs - 2024 - Cognitive Science 48 (9):e13498.
    Visual working memory (VWM) refers to the temporary storage and manipulation of visual information. Although visually different, objects we view and remember can share the same higher-level category information, such as an apple, orange, and banana all being classified as fruit. We study the influence of category information on VWM, focusing on the question of whether stimulus category coherence (i.e., whether all to-be-remembered items belong to the same semantic category) influences VWM performance. This question is addressed in two behavioral experiments (...)
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  15.  10
    Semantic influence on visual working memory of object identity and location.Ruoyang Hu & Robert A. Jacobs - 2021 - Cognition 217 (C):104891.
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  16.  41
    Integrated Approaches to Perceptual Learning.Robert A. Jacobs - 2010 - Topics in Cognitive Science 2 (2):182-188.
    New technologies and new ways of thinking have recently led to rapid expansions in the study of perceptual learning. We describe three themes shared by many of the nine articles included in this topic on Integrated Approaches to Perceptual Learning. First, perceptual learning cannot be studied on its own because it is closely linked to other aspects of cognition, such as attention, working memory, decision making, and conceptual knowledge. Second, perceptual learning is sensitive to both the stimulus properties of the (...)
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  17.  7
    Modularity and Plasticity are Compatible.Robert A. Jacobs - 1996 - In Garrison W. Cottrell (ed.), Proceedings of the Eighteenth Annual Conference of The Cognitive Science Society. Lawrence Erlbaum. pp. 18--43.
  18.  12
    Opinion-Box 1. ME architectures and inhibitory interactions.Robert A. Jacobs - 1999 - Trends in Cognitive Sciences 3 (1):31-38.
  19. Modular and hierarchical learning systems.Michael I. Jordan & Robert A. Jacobs - 1995 - In Michael A. Arbib (ed.), Handbook of Brain Theory and Neural Networks. MIT Press. pp. 579--582.
     
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  20. Are People Successful at Learning Sequences of Actions on a Perceptual Matching Task?Reiko Yakushijin & Robert A. Jacobs - 2011 - Cognitive Science 35 (5):939-962.
    We report the results of an experiment in which human subjects were trained to perform a perceptual matching task. Subjects were asked to manipulate comparison objects until they matched target objects using the fewest manipulations possible. An unusual feature of the experimental task is that efficient performance requires an understanding of the hidden or latent causal structure governing the relationships between actions and perceptual outcomes. We use two benchmarks to evaluate the quality of subjects’ learning. One benchmark is based on (...)
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  21.  13
    (1 other version)M. 1. Jordan, and AG Barto. Task decomposition through competition in a modular connectionist architecture: The what and where vision task. [REVIEW]Robert A. Jacobs - 1990 - Cognitive Science 15 (2):219-250.
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