暂无分享,去创建一个
Tom M. Mitchell | Barnabas Poczos | Leila Wehbe | Mariya Toneva | Otilia Stretcu | Tom Michael Mitchell | B. Póczos | Leila Wehbe | Mariya Toneva | Otilia Stretcu
[1] N. Kanwisher,et al. Visual attention: Insights from brain imaging , 2000, Nature Reviews Neuroscience.
[2] Radoslaw Martin Cichy,et al. The representational dynamics of task and object processing in humans , 2018, eLife.
[3] J. Gallant,et al. Reconstructing Visual Experiences from Brain Activity Evoked by Natural Movies , 2011, Current Biology.
[4] Alexander G. Huth,et al. Incorporating Context into Language Encoding Models for fMRI , 2018, bioRxiv.
[5] D. Heeger,et al. Categorical Clustering of the Neural Representation of Color , 2013, The Journal of Neuroscience.
[6] Samuel A. Nastase,et al. Attention Selectively Reshapes the Geometry of Distributed Semantic Representation , 2016, bioRxiv.
[7] J. Duncan. Attention, intelligence, and the frontal lobes. , 1995 .
[8] William W. Graves,et al. Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. , 2009, Cerebral cortex.
[9] Donald T Stuss,et al. Frontal lobes and attention: Processes and networks, fractionation and integration , 2006, Journal of the International Neuropsychological Society.
[10] Thomas L. Griffiths,et al. Supplementary Information for Natural Speech Reveals the Semantic Maps That Tile Human Cerebral Cortex , 2022 .
[11] Yi Zeng,et al. Representational similarity analysis reveals task-dependent semantic influence of the visual word form area , 2018, Scientific Reports.
[12] Leila Wehbe,et al. Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain) , 2019, NeurIPS.
[13] Gustavo Sudre,et al. Characterizing the Spatiotemporal Neural Representation of Concrete Nouns Across Paradigms , 2015 .
[14] Tom Michael Mitchell,et al. Predicting Human Brain Activity Associated with the Meanings of Nouns , 2008, Science.
[15] Y. Benjamini,et al. Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .
[16] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[17] Peter Hagoort,et al. MUC (Memory, Unification, Control) and beyond , 2013, Front. Psychol..
[18] C. Büchel,et al. Effect of language task demands on the neural response during lexical access: a functional magnetic resonance imaging study , 2013, Brain and Behavior.
[19] D. Poeppel,et al. Neural basis of speech perception. , 2015, Handbook of clinical neurology.
[20] R. Salmelin,et al. Distinct time courses of word and context comprehension in the left temporal cortex. , 1998, Brain : a journal of neurology.
[21] R'emi Louf,et al. HuggingFace's Transformers: State-of-the-art Natural Language Processing , 2019, ArXiv.
[22] M. Kiefer,et al. Perceptual and semantic sources of category-specific effects: Event-related potentials during picture and word categorization , 2001, Memory & cognition.
[23] Nikolaus Kriegeskorte,et al. Frontiers in Systems Neuroscience Systems Neuroscience , 2022 .
[24] James L. McClelland,et al. On the control of automatic processes: a parallel distributed processing account of the Stroop effect. , 1990, Psychological review.
[25] Lance J. Rips,et al. Structure and process in semantic memory: A featural model for semantic decisions. , 1974 .
[26] S. Taulu,et al. Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements , 2006, Physics in medicine and biology.
[27] Peter Hagoort,et al. The meaning-making mechanism(s) behind the eyes and between the ears , 2019, Philosophical Transactions of the Royal Society B.
[28] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[29] Riitta Salmelin,et al. Tracking neural coding of perceptual and semantic features of concrete nouns , 2012, NeuroImage.
[30] Martin Luessi,et al. MEG and EEG data analysis with MNE-Python , 2013, Front. Neuroinform..
[31] Alexander G. Huth,et al. Attention During Natural Vision Warps Semantic Representation Across the Human Brain , 2013, Nature Neuroscience.
[32] Tom M. Mitchell,et al. Aligning context-based statistical models of language with brain activity during reading , 2014, EMNLP.
[33] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[34] Yejin Choi,et al. Do Neural Language Representations Learn Physical Commonsense? , 2019, CogSci.
[35] Angela D. Friederici,et al. The ontogeny of the cortical language network , 2016, Nature Reviews Neuroscience.
[36] Jungo Kasai,et al. Understanding Commonsense Inference Aptitude of Deep Contextual Representations , 2019, Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing.
[37] Tom M. Mitchell,et al. Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition , 2013, CoNLL.
[38] Jia-Hong Gao,et al. Doctor, Teacher, and Stethoscope: Neural Representation of Different Types of Semantic Relations , 2018, The Journal of Neuroscience.
[39] Phil Blunsom,et al. Teaching Machines to Read and Comprehend , 2015, NIPS.