An Artificial Neural Network (ANN) is defined as a computational model that imitates the functioning of biological neurons. It consists of input, hidden, and output layers, processing molecular information to p
Artificial neural networks (ANNs) are massively parallel systems with large numbers of interconnected simple processors. This paper describes a computational model to support decision-making using a combination of data mining (DM) and artificial neural network (ANN). With the enormous amount of data ...
To address this question, we used such benchmarks to evaluate the visual and auditory models described above in Figs.2–5. For the visual models, we used the Brain-Score platform to measure the similarity of model representations to neural benchmarks for visual areas V1, V2 and V4 and th...
The goal was always to sequentially train the neural network on all tasks or episodes of the task protocol, whereby the network only had access to the data of the current task/episode. For all methods considered in this paper, during training the parameters θ of the neural network were upda...
Artificial Neural Network Architectures (ANN) Initially introduced by McCulloch and Pitts (1943) and in the form of a simple perceptron by Rosenblatt (1958), ANNs have gained major traction in the AI community. ANNs are highly applicable in the domain of statistical machine learning in which the...
Importantly, the question of whether AGI can be created -- and the consequences of doing so --remains hotly debatedamong AI experts. Even today's most advanced AI technologies, such as ChatGPT and other highly capable LLMs, do not demonstrate cognitive abilities on par with humans and cannot...
Alan Turing publishesComputing Machinery and Intelligence. In this paper, Turing famous for breaking the German ENIGMA code during WWII and often referred to as the "father of computer science" asks the following question: "Can machines think?" ...
Following the conventions of Keras, a question mark refers to an existing dimension of unknown size which here denotes the batch size and Lambda layers refer to user defined functions inside the network architecture. Here, the input is given by the deformation gradient F. The precise number of ...
Neural Question Generation (NQG) Automatic Question Generation (AQG) refers to the process of automatically generatingquestionsfrom a given inputcontext. Neural Question Generation (NQG) is a specific form of AQG that utilizesneural network-based models for question generation. ...
This paper explores the important role of critical science, and in particular of post-colonial and decolonial theories, in understanding and shaping the on