Live Science

'Thermodynamic computer' can mimic AI neural networks — using orders of magnitude less energy to generate images

Scientists have built a "thermodynamic computer" that can produce images from random disturbances in data, that is, noise. In ...
Hosted on MSN

Activation functions in neural networks: Types and examples

In this video, we will see What is Activation Function in Neural network, types of Activation function in Neural Network, why to use an Activation Function and which Activation function to use. The ...
eLife

Barcode activity in a recurrent network model of the hippocampus enables efficient memory binding

This fundamental work substantially advances our understanding of episodic memory by proposing a biologically plausible mechanism through which hippocampal barcode activity enables efficient memory ...
Hosted on MSN

What Is An Rnn? Recurrent Neural Networks Made Simple

in this video, we will understand what is Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural Language Processing tasks. It can be ...
GitHub

hyperparameter-tuning

Spearmint integrated Bayesian Optimization for hyper parameter tuning of Auto sparse encoder embedded with softmax Classifier for MNIST digit Classification. Platform + GUI for hyperparameter ...
Scientific Research Publishing

Chung, J., Gulcehre, C., Cho, K. and Bengio, Y. (2014) Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
IEEE

A Novel Adaptive Recurrent Neural Network-Based Control Strategy for Type 3 WF to Mitigate Subsynchronous Interactions

Abstract: The interaction between the wind farm (WF) and the series-compensated long transmission line may cause subsynchronous interaction (SSI) phenomenon. The conventional subsynchronous damping ...
IEEE

Lithium-Ion Battery State-of-Charge and State-of-Energy Simultaneous Estimation via Sparse- Quasi Recurrent Neural Networks(S-QRNN)

Abstract: This paper presents an innovative methodology for the concurrent estimation of Lithium-Ion Battery (LiB) State-of-Charge (SoC) and State-of-Energy (SoE) employing Sparse Quasi-Recurrent ...