Search Results - Miconi, Thomas

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  1. 1
    Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks

    Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks by Miconi, Thomas

    Published in eLife
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  2. 2
    A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure

    A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure by Miconi, Thomas, VanRullen, Rufin

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  3. 3
    There's Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task

    There's Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task by Miconi, Thomas, Groomes, Laura, Kreiman, Gabriel

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  4. 4
    Spontaneous emergence of fast attractor dynamics in a model of developing primary visual cortex

    Spontaneous emergence of fast attractor dynamics in a model of developing primary visual cortex by Miconi, Thomas, McKinstry, Jeffrey L., Edelman, Gerald M.

    Published in Nature communications
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  5. 5
    The gamma slideshow: object-based perceptual cycles in a model of the visual cortex

    The gamma slideshow: object-based perceptual cycles in a model of the visual cortex by Miconi, Thomas, Vanrullen, Rufin

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  6. 6
    A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure: e1004770

    A Feedback Model of Attention Explains the Diverse Effects of Attention on Neural Firing Rates and Receptive Field Structure: e1004770 by Miconi, Thomas, VanRullen, Rufin

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  7. 7
    Evosphere: Evolutionary dynamics in a population of fighting virtual creatures

    Evosphere: Evolutionary dynamics in a population of fighting virtual creatures by Miconi, T.

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  8. 8
    Defining and simulating open-ended novelty: requirements, guidelines, and challenges

    Defining and simulating open-ended novelty: requirements, guidelines, and challenges by Banzhaf, Wolfgang, Baumgaertner, Bert, Beslon, Guillaume, Doursat, René, Foster, James A., McMullin, Barry, de Melo, Vinicius Veloso, Miconi, Thomas, Spector, Lee, Stepney, Susan, White, Roger

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  9. 9
    Procedural generation of meta-reinforcement learning tasks

    Procedural generation of meta-reinforcement learning tasks by Miconi, Thomas

    Published in arXiv.org
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  10. 10
    Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning

    Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learning by Miconi, Thomas

    Published in arXiv.org
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  11. 11
    Hebbian learning with gradients: Hebbian convolutional neural networks with modern deep learning frameworks

    Hebbian learning with gradients: Hebbian convolutional neural networks with modern deep learning frameworks by Miconi, Thomas

    Published in arXiv.org
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  12. 12
    Enabling Continual Learning with Differentiable Hebbian Plasticity

    Enabling Continual Learning with Differentiable Hebbian Plasticity by Thangarasa, Vithursan, Miconi, Thomas, Taylor, Graham W.

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  13. 13
    The impossibility of "fairness": a generalized impossibility result for decisions

    The impossibility of "fairness": a generalized impossibility result for decisions by Miconi, Thomas

    Published in arXiv.org
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  14. 14
    Learning to learn with backpropagation of Hebbian plasticity

    Learning to learn with backpropagation of Hebbian plasticity by Miconi, Thomas

    Published in arXiv.org
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  15. 15
    Neural networks with differentiable structure

    Neural networks with differentiable structure by Miconi, Thomas

    Published in arXiv.org
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  16. 16
    Training recurrent neural networks with sparse, delayed rewards for flexible decision tasks

    Training recurrent neural networks with sparse, delayed rewards for flexible decision tasks by Miconi, Thomas

    Published in arXiv.org
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  17. 17
    The N-Strikes-Out Algorithm: A Steady-State Algorithm for Coevolution

    The N-Strikes-Out Algorithm: A Steady-State Algorithm for Coevolution by Miconi, T., Channon, A.

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  18. 18
    Enabling Continual Learning with Differentiable Hebbian Plasticity

    Enabling Continual Learning with Differentiable Hebbian Plasticity by Thangarasa, Vithursan, Miconi, Thomas, Taylor, Graham W

    Published in arXiv.org
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  19. 19
    A virtual creatures model for studies in artificial evolution

    A virtual creatures model for studies in artificial evolution by Miconi, T., Channon, A.

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  20. 20
    Brain-inspired learning in artificial neural networks: a review

    Brain-inspired learning in artificial neural networks: a review by Schmidgall, Samuel, Achterberg, Jascha, Miconi, Thomas, Kirsch, Louis, Ziaei, Rojin, Hajiseyedrazi, S Pardis, Eshraghian, Jason

    Published in arXiv.org
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