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Machine learning to emulate components of ECMWF’s Integrated Forecasting System 新闻
来源平台:European Centre for Medium-Range Weather Forecasts. 发布日期:2021
作者:  admin
收藏  |  浏览/下载:35/0  |  提交时间:2021/12/15
Manipulating neuronal circuits, in concert 期刊论文
Science, 2021
作者:  Weijian Yang
收藏  |  浏览/下载:15/0  |  提交时间:2021/08/10
Increasing the memory capacity of intelligent systems based on the function of human neurons 新闻
来源平台:EurekAlert. 发布日期:2021
作者:  admin
收藏  |  浏览/下载:19/0  |  提交时间:2021/06/15
Upscaling reactive transport and clogging in shale microcracks by deep learning 期刊论文
Water Resources Research, 2021
作者:  Ziyan Wang;  Ilenia Battiato
收藏  |  浏览/下载:2/0  |  提交时间:2021/04/06
Deep learning: A new engine for ecological resource research 新闻
来源平台:EurekAlert. 发布日期:2020
作者:  admin
收藏  |  浏览/下载:3/0  |  提交时间:2020/05/26
Leveraging machine learning for predicting flash flood damage in the Southeast US 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (2)
作者:  Alipour, Atieh;  Ahmadalipour, Ali;  Abbaszadeh, Peyman;  Moradkhani, Hamid
收藏  |  浏览/下载:10/0  |  提交时间:2020/07/02
flash flood  risk  flood damage  machine learning  
Recurrent interactions in local cortical circuits 期刊论文
NATURE, 2020, 579 (7798) : 256-+
作者:  Liu, Yang;  Nguyen, Phong T.;  Wang, Xun;  Zhao, Yuting;  Meacham, Corbin E.;  Zou, Zhongju;  Bordieanu, Bogdan;  Johanns, Manuel;  Vertommen, Didier;  Wijshake, Tobias;  May, Herman;  Xiao, Guanghua;  Shoji-Kawata, Sanae;  Rider, Mark H.
收藏  |  浏览/下载:8/0  |  提交时间:2020/07/03

Most cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing pattern completion and other computations(1-4). Cortical circuits contain subnetworks that consist of neurons with similar receptive fields and increased connectivity relative to the network average(5,6). Cortical neurons that encode different types of information are spatially intermingled and distributed over large brain volumes(5-7), and this complexity has hindered attempts to probe the function of these subnetworks by perturbing them individually(8). Here we use computational modelling, optical recordings and manipulations to probe the function of recurrent coupling in layer 2/3 of the mouse vibrissal somatosensory cortex during active tactile discrimination. A neural circuit model of layer 2/3 revealed that recurrent excitation enhances sensory signals by amplification, but only for subnetworks with increased connectivity. Model networks with high amplification were sensitive to damage: loss of a few members of the subnetwork degraded stimulus encoding. We tested this prediction by mapping neuronal selectivity(7) and photoablating(9,10) neurons with specific selectivity. Ablation of a small proportion of layer 2/3 neurons (10-20, less than 5% of the total) representing touch markedly reduced responses in the spared touch representation, but not in other representations. Ablations most strongly affected neurons with stimulus responses that were similar to those of the ablated population, which is also consistent with network models. Recurrence among cortical neurons with similar selectivity therefore drives input-specific amplification during behaviour.


Computational modelling, imaging and single-cell ablation in layer 2/3 of the mouse vibrissal somatosensory cortex reveals that recurrent activity in cortical neurons can drive input-specific amplification during behaviour.


  
A Machine-Learning Approach for Earthquake Magnitude Estimation 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2020, 47 (1)
作者:  Mousavi, S. Mostafa;  Beroza, Gregory C.
收藏  |  浏览/下载:8/0  |  提交时间:2020/07/02
Deep Learning Models Augment Analyst Decisions for Event Discrimination 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2019, 46 (7) : 3643-3651
作者:  Linville, Lisa;  Pankow, Kristine;  Draelos, Timothy
收藏  |  浏览/下载:6/0  |  提交时间:2019/11/26
Utah  event classification  event discrimination  deep learning  convolutional neural network  recurrent neural network  
Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural NetworksN 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2018, 123 (22) : 12543-12563
作者:  Asanjan, Ata Akbari;  Yang, Tiantian;  Hsu, Kuolin;  Sorooshian, Soroosh;  Lin, Junqiang;  Peng, Qidong
收藏  |  浏览/下载:5/0  |  提交时间:2019/04/09