The neural and cognitive architecture for learning from a small sample

[1]  Yuan Chang Leong,et al.  Dynamic Interaction between Reinforcement Learning and Attention in Multidimensional Environments , 2017, Neuron.

[2]  Selen Atasoy,et al.  Human brain networks function in connectome-specific harmonic waves , 2016, Nature Communications.

[3]  Peter Dayan,et al.  A Neural Substrate of Prediction and Reward , 1997, Science.

[4]  Paul H. E. Tiesinga,et al.  Feature Specific Prediction Errors and Surprise across Macaque Fronto-Striatal Circuits during Attention and Learning , 2018 .

[5]  T. Robbins,et al.  Compulsivity Reveals a Novel Dissociation between Action and Confidence , 2017, Neuron.

[6]  Kimberly L. Stachenfeld,et al.  The hippocampus as a predictive map , 2017, Nature Neuroscience.

[7]  Bhaskara Marthi,et al.  A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs , 2017, Science.

[8]  S. Shomstein,et al.  The Differential Effects of Reward on Space- and Object-Based Attentional Allocation , 2013, The Journal of Neuroscience.

[9]  Christopher D. Manning,et al.  Compositional Attention Networks for Machine Reasoning , 2018, ICLR.

[10]  M. Kawato,et al.  Non-commercial Research and Educational Use including without Limitation Use in Instruction at Your Institution, Sending It to Specific Colleagues That You Know, and Providing a Copy to Your Institution's Administrator. All Other Uses, Reproduction and Distribution, including without Limitation Comm , 2022 .

[11]  Sarah L Parylak,et al.  Dopaminergic inputs in the dentate gyrus direct the choice of memory encoding , 2016, Proceedings of the National Academy of Sciences.

[12]  Blake A. Richards,et al.  The Persistence and Transience of Memory , 2017, Neuron.

[13]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  Jack J. Lin,et al.  Encoding of Multiple Reward-Related Computations in Transient and Sustained High-Frequency Activity in Human OFC , 2018, Current Biology.

[15]  Joseph T. McGuire,et al.  Functionally Dissociable Influences on Learning Rate in a Dynamic Environment , 2014, Neuron.

[16]  Alexandre Pouget,et al.  Confidence and certainty: distinct probabilistic quantities for different goals , 2016, Nature Neuroscience.

[17]  K. Doya,et al.  Neural substrate of dynamic Bayesian inference in the cerebral cortex , 2016, Nature Neuroscience.

[18]  Yoshua Bengio,et al.  Show, Attend and Tell: Neural Image Caption Generation with Visual Attention , 2015, ICML.

[19]  Guigang Zhang,et al.  Deep Learning , 2016, Int. J. Semantic Comput..

[20]  Yoshua Bengio.  The Consciousness Prior , 2017, ArXiv.

[21]  Yoshua Bengio,et al.  Generative Adversarial Nets , 2014, NIPS.

[22]  Joel Z. Leibo,et al.  Prefrontal cortex as a meta-reinforcement learning system , 2018, bioRxiv.

[23]  Blake A. Richards,et al.  Memory Transformation Enhances Reinforcement Learning in Dynamic Environments , 2016, The Journal of Neuroscience.

[24]  Nicolas W. Schuck,et al.  Human Orbitofrontal Cortex Represents a Cognitive Map of State Space , 2016, Neuron.

[25]  J. Matias Palva,et al.  High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention , 2017, NeuroImage.

[26]  Scott Cheng-Hsin Yang,et al.  Theoretical perspectives on active sensing , 2016, Current Opinion in Behavioral Sciences.

[27]  Timothy E. J. Behrens,et al.  Organizing conceptual knowledge in humans with a gridlike code , 2016, Science.

[28]  Zoubin Ghahramani,et al.  Probabilistic machine learning and artificial intelligence , 2015, Nature.

[29]  Joshua B. Tenenbaum,et al.  Building machines that learn and think like people , 2016, Behavioral and Brain Sciences.

[30]  Sumio Watanabe.  Algebraic Geometry and Statistical Learning Theory , 2009 .

[31]  Sergio Gomez Colmenarejo,et al.  Hybrid computing using a neural network with dynamic external memory , 2016, Nature.

[32]  A. Pouget,et al.  Information-limiting correlations , 2014, Nature Neuroscience.

[33]  S. Dehaene,et al.  What is consciousness, and could machines have it? , 2017, Science.

[34]  Joshua B. Tenenbaum,et al.  Human-level concept learning through probabilistic program induction , 2015, Science.

[35]  Demis Hassabis,et al.  Mastering the game of Go with deep neural networks and tree search , 2016, Nature.

[36]  James L. McClelland,et al.  What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated , 2016, Trends in Cognitive Sciences.

[37]  Demis Hassabis,et al.  SCAN: Learning Abstract Hierarchical Compositional Visual Concepts , 2017, ArXiv.

[38]  Earl K. Miller,et al.  Different Levels of Category Abstraction by Different Dynamics in Different Prefrontal Areas , 2018, Neuron.

[39]  Caitlin R. Bowman,et al.  Abstract Memory Representations in the Ventromedial Prefrontal Cortex and Hippocampus Support Concept Generalization , 2018, The Journal of Neuroscience.

[40]  Christopher D. Manning,et al.  Effective Approaches to Attention-based Neural Machine Translation , 2015, EMNLP.

[41]  E. Miller,et al.  Goal-direction and top-down control , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[42]  M. Carandini,et al.  Subcortical Source and Modulation of the Narrowband Gamma Oscillation in Mouse Visual Cortex , 2016, Neuron.

[43]  Daeyeol Lee,et al.  Feature-based learning improves adaptability without compromising precision , 2017, Nature Communications.

[44]  Mitsuo Kawato,et al.  Heterarchical reinforcement-learning model for integration of multiple cortico-striatal loops: fMRI examination in stimulus-action-reward association learning , 2006, Neural Networks.

[45]  H. Kennedy,et al.  Visual Areas Exert Feedforward and Feedback Influences through Distinct Frequency Channels , 2014, Neuron.

[46]  E. Rolls,et al.  Confidence-related decision making. , 2010, Journal of neurophysiology.

[47]  József Fiser,et al.  Neural Variability and Sampling-Based Probabilistic Representations in the Visual Cortex , 2016, Neuron.

[48]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[49]  J. O'Keefe,et al.  The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. , 1971, Brain research.

[50]  Dmitry Berenson,et al.  What Happened at the DARPA Robotics Challenge Finals , 2018 .

[51]  S. Grossberg.  Contour Enhancement , Short Term Memory , and Constancies in Reverberating Neural Networks , 1973 .

[52]  B. Staresina,et al.  Hippocampal pattern completion is linked to gamma power increases and alpha power decreases during recollection , 2016, eLife.

[53]  A M Graybiel,et al.  The basal ganglia and adaptive motor control. , 1994, Science.

[54]  M. Kawato,et al.  Multivoxel neurofeedback selectively modulates confidence without changing perceptual performance , 2016, Nature Communications.

[55]  M. Kawato,et al.  New insights into olivo-cerebellar circuits for learning from a small training sample , 2017, Current Opinion in Neurobiology.

[56]  Robert C. Wilson,et al.  An Approximately Bayesian Delta-Rule Model Explains the Dynamics of Belief Updating in a Changing Environment , 2010, The Journal of Neuroscience.

[57]  Alex Graves,et al.  Neural Turing Machines , 2014, ArXiv.

[58]  Joel Z. Leibo,et al.  Unsupervised Predictive Memory in a Goal-Directed Agent , 2018, ArXiv.

[59]  Keisuke Yamazaki,et al.  Asymptotic accuracy of distribution-based estimation of latent variables , 2012, J. Mach. Learn. Res..

[60]  Geoffrey E. Hinton,et al.  Adaptive Mixtures of Local Experts , 1991, Neural Computation.

[61]  Peter Dayan,et al.  Hippocampal Contributions to Control: The Third Way , 2007, NIPS.

[62]  P. Sterzer,et al.  Mesolimbic confidence signals guide perceptual learning in the absence of external feedback , 2016, eLife.

[63]  Jian Sun,et al.  Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[64]  Michael L. Mack,et al.  Dynamic updating of hippocampal object representations reflects new conceptual knowledge , 2016, Proceedings of the National Academy of Sciences.

[65]  Nicolas Y. Masse,et al.  Task-specific versus generalized mnemonic representations in parietal and prefrontal cortices , 2015, Nature Neuroscience.

[66]  Thilo Womelsdorf,et al.  Feature-specific prediction errors and surprise across macaque fronto-striatal circuits , 2018, bioRxiv.

[67]  Karl J. Friston,et al.  Active Inference, Curiosity and Insight , 2017, Neural Computation.

[68]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[69]  渡邊 澄夫.  Algebraic geometry and statistical learning theory , 2009 .

[70]  M. Botvinick,et al.  The hippocampus as a predictive map , 2016 .

[71]  G. Buzsáki,et al.  Neuronal Oscillations in Cortical Networks , 2004, Science.