GitHub

Infosys Model Inference Library

The Infosys Model Inference Library (IMIL) is a versatile and powerful tool designed to simplify the deployment and utilization of machine learning models, regardless of the framework or model type.
Scientific Research Publishing

Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms ()

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.
IEEE

Constrained Fractional-Order Model Predictive Control for Robust Path Following of FWID-AGVs With Asymptotic Prescribed Performance

Abstract: This paper proposes a prescribed performance function (PPF)-based constrained fractional-order model predictive controller (CFMPC) for the robust path following of the four-wheel-independent ...
IEEE

Multi-Agent Reinforcement Learning With Spatial Structure Awareness for Topological Map-Based Path-Finding

Efficient Multi-Agent Path Finding (MAPF) is pivotal for warehouse logistics. While existing learning-based methods primarily rely on computationally intensive grid-based representations, topological ...