AI develops easily understandable solutions for unusual experiments in quantum physics

Researchers at the University of Tuebingen, working with an international team, have developed an artificial intelligence that designs entirely new, sometimes unusual, experiments in quantum physics ...
InfoWorld

How to choose the best LLM using R and vitals

Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models ...
Hosted on MSN

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 ...
GitHub

Recurrent Neural Network (RNN) Introduction

RNN stands for recurrent neural network. It is one of the classic architectures for modeling sequences. RNN is simple, but learning it can help us understand the foundations, such as encoding, loss ...
GitHub

Farhannr28/Convolutional-Neural-Network-and-Recurrent-Neural-Network

Program ini dibuat untuk menyelesaikan Tugas Besar 2 IF3270 Pembelajaran Mesin. Program ini berisi implementasi dari Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), dan Long-Short ...
Scientific Research Publishing

Medsker, L.R. and Jain, L. (2001) Recurrent Neural Networks: Design and Applications. CRC Press.

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 ...
IEEE

Analysis Cryptocurrency Prediction Price Using Recurrent Neural Network (RNN) Gate Recurrent Unit (GRU) Long Short-Term Memory (LSTM)

Abstract: Cryptocurrencies, which are digital assets intended to function as a medium of electronic exchange, have garnered significant global attention, with Bitcoin standing out as the most ...
IEEE

Stability and Performance Analysis of Discrete-Time ReLU Recurrent Neural Networks

Abstract: This paper presents sufficient conditions for the stability and $\ell_{2}$-gain performance of recurrent neural networks (RNNs) with ReLU activation functions. These conditions are derived ...