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Neuroscience 논문 리뷰
Neuroscience 분야 주요 연구 논문을 연구 동기·방법·결과로 구조화한 AI 논문 리뷰 목록입니다.
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필터
2,181개의 결과
How (not) to assess the importance of correlations for the matching of spontaneous and evoked activity
József Fiser, Máté Lengyel 외 3명
arXiv (Cornell University)
|
2013
|
7 회 인용
Information flow between resting state networks
Ibai Díez, Asier Erramuzpe 외 7명
arXiv (Cornell University)
|
2015
|
7 회 인용
Intent Recognition in Smart Living Through Deep Recurrent Neural Networks
Xiang Zhang, Lina Yao 외 3명
arXiv (Cornell University)
|
2017
|
7 회 인용
Inter-Subject Analysis: Inferring Sparse Interactions with Dense Intra-Graphs
Cong Ma, Junwei Lu 외 1명
arXiv (Cornell University)
|
2017
|
7 회 인용
Interactions between Intrinsic and Stimulus-Evoked Activity in Recurrent Neural Networks
L F Abbott, Kanaka Rajan 외 1명
arXiv (Cornell University)
|
2009
|
7 회 인용
Interval timing in deep reinforcement learning agents
Ben Deverett, Ryan Faulkner 외 3명
arXiv (Cornell University)
|
2019
|
7 회 인용
Introduction: Toward an interdisciplinary science of spontaneous thought
Kieran C. R. Fox, Kalina Christoff
arXiv (Cornell University)
|
2017
|
7 회 인용
Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?
Numan Saeed, Shahad Hardan 외 2명
arXiv (Cornell University)
|
2022
|
7 회 인용
Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons
Paul Haider, Benjamin Ellenberger 외 4명
arXiv (Cornell University)
|
2021
|
7 회 인용
Latent Space Analysis of VAE and Intro-VAE applied to 3-dimensional MR Brain Volumes of Multiple Sclerosis, Leukoencephalopathy, and Healthy Patients
Christopher Vogelsanger, Christian Federau
arXiv (Cornell University)
|
2021
|
7 회 인용
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