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ORCID1st EXPLAINS 2024: Porto, Portugal
- Francesco Marcelloni, Kurosh Madani, Niki van Stein, Joaquim Filipe:
Proceedings of the 1st International Conference on Explainable AI for Neural and Symbolic Methods, EXPLAINS 2024, Porto, Portugal, November 20-22, 2024. SCITEPRESS 2024, ISBN 978-989-758-720-7
Invited Speakers
- Tome Eftimov:
Trustworthy Benchmarking for Black-Box Single-Objective Optimization. EXPLAINS 2024: 5 - Gabriela Ochoa:
Search Trajectories Illuminated. EXPLAINS 2024: 7 - Rita P. Ribeiro:
Predictive Maintenance for Industry 4.0 & 5.0. EXPLAINS 2024: 9
Papers
- Lars Fluri
:
Feature Importance for Deep Neural Networks: A Comparison of Predictive Power, Infidelity and Sensitivity. 15-26 - Mattia Daole, Pietro Ducange, Francesco Marcelloni, Giustino Claudio Miglionico, Alessandro Renda, Alessio Schiavo:
XAIMed: A Diagnostic Support Tool for Explaining AI Decisions on Medical Images. 27-37 - Alexandre Moreira, Artur Ferreira, Nuno Leite:
Prediction of Alzheimer Disease on the DARWIN Dataset with Dimensionality Reduction and Explainability Techniques. 38-49 - Simone Bertolotto, André Panisson, Alan Perotti:
LLM-Generated Class Descriptions for Semantically Meaningful Image Classification. 50-61 - Qi Huang, Sofoklis Kitharidis, Thomas Bäck, Niki van Stein:
TX-Gen: Multi-Objective Optimization for Sparse Counterfactual Explanations for Time-Series Classification. 62-74 - Devon Tao, Lucas Bang:
Fitness Landscape Analysis of a Cell-Based Neural Architecture Search Space. 77-86 - Sony K. Ahuja, Deepti D. Shrimankar, Aditi R. Durge:
Design of an Iterative Method for Deep Multimodal Feature Fusion in Heart Disease Diagnostics Utilizing Explainable AI. 87-95 - Torben Logemann, Eric M. S. P. Veith:
Analyzing Exact Output Regions of Reinforcement Learning Policy Neural Networks for High-Dimensional Input-Output Spaces. 96-107 - Giustino Claudio Miglionico, Pietro Ducange, Francesco Marcelloni, Witold Pedrycz:
Deep Learning and Multi-Objective Evolutionary Fuzzy Classifiers: A Comparative Analysis for Brain Tumor Classification in MRI Images. 108-115 - Sergei Nirenburg, Marjorie McShane, Kenneth W. Goodman, Sanjay Oruganti:
Explaining Explaining. 116-123 - Kunyoung Kim, Donggyu Kim, Mye M. Sohn:
Graph Hierarchy and Language Model-Based Explainable Entity Alignment of Knowledge Graphs. 124-131 - Arman Zafaranchi, Francesca Lizzi, Alessandra Retico, Camilla Scapicchio, Maria Evelina Fantacci:
Explainability Applied to a Deep-Learning Based Algorithm for Lung Nodule Segmentation. 132-138 - Viacheslav E. Antsiperov:
Neuromorphic Encoding / Decoding of Data-Event Streams Based on the Poisson Point Process Model. 139-146 - N. Nisbet, Joanna Isabelle Olszewska:
Computer Vision Based Smart Security System for Explainable Edge Computing. 147-154
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