This simple ChatGPT prompt makes AI teach instead of lecture

Instead of just giving you a knowledge dump, this prompt turns an AI chatbot into a teacher trained in the Socratic method.
IEEE

Deep Simple Recurrent Unit-Based Transient Modeling Method for High-Speed Circuits

Abstract: The need for rapid and precise transient simulation for signal integrity (SI) assessment of high-speed circuits in microwave systems becomes increasingly crucial. Conventional recurrent ...
GitHub

Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras

Time series prediction problems are a difficult type of predictive modeling problem. Unlike regression predictive modeling, time series also adds the complexity of a sequence dependence among the ...
eLife

MotorNet: a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks

The authors present "MotorNet", a useful software package to train artificial neural networks to control a biomechanical model of an effector. The manuscript provides solid evidence that MotorNet is ...
IEEE

Chaotic dynamics in quasi-layered recurrent neural network model and application to complex control via simple rule

Abstract: In this paper, chaotic dynamics in quasi-layered recurrent neural network model (QLRNNM), consisting of sensory neurons and motor neurons, is applied to solving ill-posed problems. We would ...
Scientific Research Publishing

Srivastava, N., Hinton, G.E., Krizhevsky, A., et al. (2014) Dropout: A Simple Way to Prevent Neural Networks from Overfitting. Journal of Machine Learning Research, 15, 1929-1958.

ABSTRACT: Five-electrode configurations were designed to simulate the distribution inhomogeneity of electric field intensities in the air-insulating medium, and the characteristic data waveforms of ...
PNAS

Simple framework for constructing functional spiking recurrent neural networks

Recent advances in artificial intelligence and deep learning have significantly improved the capability of recurrently connected artificial neural networks. Although these networks can achieve high ...