Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

Almost every tech organization is moving towards AI. The demand for skilled AI professionals has reached in a exponential rate. The global AI market is projecte ...

We present a tutorial for MCMC methods that covers simple Bayesian linear and logistic models, and Bayesian neural networks. The aim of this tutorial is to bridge the gap between theory and ...

Hands-on coding of a multiclass neural network from scratch, with softmax and one-hot encoding. #Softmax #MulticlassClassification #PythonAI The 2 House Republicans who voted no on Trump's ...

This repository contains my implementation of a feed-forward neural network classifier in Python and Keras, trained on the Fashion-MNIST dataset. It closely follows the tutorial by The Clever ...

This repository contains my implementation of a feed-forward neural network classifier in Python and Keras, trained on the Fashion-MNIST dataset. It closely follows the tutorial by The Clever ...

Thus, we present a new class of accurate and efficient statistical models for large neural population codes that also suggests a clear computational benefit of homeostatic synaptic normalization and ...

MotorNet is a Python toolbox for training artificial neural networks to control arbitrarily complex, differentiable, and biomechanically realistic musculo-skeletal effectors on user-defined ...