26 citations · 42 across the 9 of their papers we have counts for
10 papers
Leveraging ChatGPT's Multimodal Vision Capabilities to Rank Satellite Images by Poverty Level: Advancing Tools for Social Science Research
Hamid Sarmadi, Ola Hall, Thorsteinn Rögnvaldsson +1
This paper investigates the novel application of Large Language Models (LLMs) with vision capabilities to analyze satellite imagery for village-level poverty prediction. Although L…
Volvo Discovery Challenge at ECML-PKDD 2024
Mahmoud Rahat, Peyman Sheikholharam Mashhadi, Sławomir Nowaczyk +6
This paper presents an overview of the Volvo Discovery Challenge, held during the ECML-PKDD 2024 conference. The challenge's goal was to predict the failure risk of an anonymized c…
Learning to Learn without Forgetting using Attention
Anna Vettoruzzo, Joaquin Vanschoren, Mohamed-Rafik Bouguelia +1
Continual learning (CL) refers to the ability to continually learn over time by accommodating new knowledge while retaining previously learned experience. While this concept is inh…
CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis
Abdallah Alabdallah, Omar Hamed, Mattias Ohlsson +2
The Cox Proportional Hazards (CPH) model has long been the preferred survival model for its explainability. However, to increase its predictive power beyond its linear log-risk, it…
Personalized Federated Learning with Contextual Modulation and Meta-Learning
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Thorsteinn Rögnvaldsson
Federated learning has emerged as a promising approach for training machine learning models on decentralized data sources while preserving data privacy. However, challenges such as…
Towards Explaining Satellite Based Poverty Predictions with Convolutional Neural Networks
Hamid Sarmadi, Thorsteinn Rögnvaldsson, Nils Roger Carlsson +3
Deep convolutional neural networks (CNNs) have been shown to predict poverty and development indicators from satellite images with surprising accuracy. This paper presents a first…
Advances and Challenges in Meta-Learning: A Technical Review
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Joaquin Vanschoren +2
Meta-learning empowers learning systems with the ability to acquire knowledge from multiple tasks, enabling faster adaptation and generalization to new tasks. This review provides…
Satellite Image and Machine Learning based Knowledge Extraction in the Poverty and Welfare Domain
Ola Hall, Mattias Ohlsson, Thortseinn Rögnvaldsson
Recent advances in artificial intelligence and machine learning have created a step change in how to measure human development indicators, in particular asset based poverty. The co…
The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models
Abdallah Alabdallah, Mattias Ohlsson, Sepideh Pashami +1
The Concordance Index (C-index) is a commonly used metric in Survival Analysis for evaluating the performance of a prediction model. In this paper, we propose a decomposition of th…
Transfer learning for Remaining Useful Life Prediction Based on Consensus Self-Organizing Models
Yuantao Fan, Sławomir Nowaczyk, Thorsteinn Rögnvaldsson
The traditional paradigm for developing machine prognostics usually relies on generalization from data acquired in experiments under controlled conditions prior to deployment of th…