Theoretical Insights into Neural Networks and Deep Learning: Advancing Understanding, Interpretability, and Generalization
UA Usmani, MU Usmani - 2023 World Conference on …, 2023 - ieeexplore.ieee.org
This work aims to provide profound insights into neural networks and deep learning,
focusing on their functioning, interpretability, and generalization capabilities. It explores …
focusing on their functioning, interpretability, and generalization capabilities. It explores …
Developing interpretable machine learning for forward kinematics of robotic arms
ST Kanneganti, JS Pei… - 2021 IEEE Symposium …, 2021 - ieeexplore.ieee.org
Machine learning (ML) is becoming increasingly sought after in diverse domains.
Unfortunately for this objective, most ML research has focused on improving performance on …
Unfortunately for this objective, most ML research has focused on improving performance on …
Pattern representations for classifying (non-) metric (non-) vectorial data with applications in Structural Health Monitoring and geotechnical/natural-hazard engineering
YM Ospina Dávila - 2022 - repositorio.unal.edu.co
Nowadays, data-driven modelling in structural and geo-engineering problems using
Statistical Pattern Recognition and Machine Learning provides powerful and more versatile …
Statistical Pattern Recognition and Machine Learning provides powerful and more versatile …
[引用][C] Informed, Interactive, and Interpretable Machine Learning for Forward Kinematics of Robot Arms
ST Kanneganti - 2022