Ireland’s Centre For AI
Publications
CeADAR Publication Library
As Ireland’s premier centre for AI, CeADAR has been at the forefront of producing influential research papers and collaborating on numerous projects across diverse industry sectors. Our work spans start-ups, spin-outs, SMEs, and multinational corporations. We boast a strong track record of securing funding for applied research projects both in Ireland and throughout Europe. These EU projects focus on collaborative efforts with technical research institutions, academic partners, and industry leaders, resulting in the publication of cutting-edge research papers that advance the field of AI.
2024
Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing
A Satellite-derived Peatland Ecotype Classification Method Using Artificial Neural Network Hierarchical Ensembles
Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge Graph
2023
Glucose Variability Analysis in Two Large-Scale and Real-World Data Sets of Open-Source Automated Insulin Delivery Systems
Long-Term Glucose Forecasting for Open-Source Automated Insulin Delivery Systems: A Machine Learning Study with Real-World Variability Analysis
Machine Learning for Financial Prediction Under Regime Change Using Technical Analysis: A Systematic Review
Towards a Framework for the Global Assessment of Sensitive Attribute Bias Within Binary Classification Algorithms
Forecasting COVID-19 cases using dynamic time warping and incremental machine learning methods
Keen to find out more about the publications above or how we might be able to support you?
2024
Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing
A Satellite-derived Peatland Ecotype Classification Method Using Artificial Neural Network Hierarchical Ensembles
Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge Graph
2023
Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing
A Satellite-derived Peatland Ecotype Classification Method Using Artificial Neural Network Hierarchical Ensembles
Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge Graph
Keen to find out more about the publications above or how we might be able to support you?