This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Abstract: In this paper, a method for inferring the motion intentions of a neighboring vehicle ahead of an ego vehicle using a physics-informed deep neural network-based open-set classification ...

A public API for HNG Stage 1 task that classifies a given number by identifying its mathematical properties (prime, perfect, Armstrong, parity, digit sum) and retrieves a fun fact using the Numbers ...

ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...

Introduction: Rapid and scalable classification of SARS-CoV-2 genomes from spike-gene sequences can support real-time genomic surveillance in contexts where whole-genome data or high-end computing ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification, according ...

Abstract: Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in ...

MAGNET is implemented in Python 3.10 and is supported on both Linux and Windows. It should work on any operating system that supports Python. The implementation has been tested on both GPU and CPU ...