Department of Brain and Cognitive Sciences & McGovern Institute, MIT, Cambridge, United States Integrative Computational Neuroscience Center and Yang-Tan Collective, MIT, Cambridge, United States ...
Machine learning is a complex discipline but implementing machine learning models is far less daunting than it used to be. Machine learning frameworks like Google’s TensorFlow ease the process of ...
This publication provides an in-depth overview of various neural network layers, including their historical development, mathematical formulations, and code implementations. We cover common layer ...
This important work provides evidence that artificial recurrent neural networks can be used to investigate neural mechanisms underlying reversible remapping of spatial representations. Authors perform ...
Understanding the neural mechanisms of working memory has been a long-standing Neuroscience goal. Bump attractor models have been used to simulate persistent activity generated in the prefrontal ...
This repository contains a PyTorch implementation of Salesforce Research's Quasi-Recurrent Neural Networks paper. The QRNN provides similar accuracy to the LSTM but can be betwen 2 and 17 times faster ...
1 Trumbull High School, Trumbull, USA. 2 University of Chicago/Computer Science, Chicago, USA. External factors, such as social media and financial news, can have wide-spread effects on stock price ...
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