The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...
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Neural network Python from scratch with softmax
Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Abstract: Discrete time-varying problems are pervasive in the fields of engineering and science. Traditional handling schemes to discrete problem often involve the intervention of continuous-time ...
This project implements a robust time series forecasting pipeline to predict the closing prices of the IBOVESPA index, Brazil’s main stock market benchmark. It combines advanced data preprocessing ...
Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks
Abstract: Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in ...
The findings of this study are valuable, offering insights into the neural representation of reversal probability in decision-making tasks, with potential implications for understanding flexible ...
ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
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