In recent years, neural network models have been widely used in many tasks, however, tampering operations from malicious attackers, e.g., backdoor attacks and parameter malicious tampering, can easily ...

This paper presents a new hierarchical deep neural network architecture with a multi-section learning mechanism for the classification of multi-output time series datasets. The hierarchical structure ...

A Hierarchical Task Network planner utilizing LLMs like OpenAI's GPT-4 to create complex plans from natural language that can be converted into an executable form.

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...

In machine learning, a hierarchical model is an approach that organises data and learning processes into layered structures.

We present an efficient and scalable partitioning method for mapping large-scale neural network models with locally dense and globally sparse connectivity onto reconfigurable neuromorphic hardware.

HiClass is an open-source Python package for local hierarchical classification that fully complies with scikit. It provides implementations of the most popular machine learning models and includes ...