Outputs (2851)

Exploring rounD Dataset for Domain Generalization in Autonomous Vehicle Trajectory Prediction (2024)
Journal Article
Zhang, Z. (2024). Exploring rounD Dataset for Domain Generalization in Autonomous Vehicle Trajectory Prediction. Sensors, 24(23), Article 7538. https://doi.org/10.3390/s24237538

This paper analyzes the rounD dataset to advance motion forecasting algorithms for autonomous vehicles navigating complex roundabout environments. We develop a trajectory prediction framework inspired by Gated Recurrent Unit (GRU) networks and graph-... Read More about Exploring rounD Dataset for Domain Generalization in Autonomous Vehicle Trajectory Prediction.

Enhanced cross-domain lithology classification in imbalanced datasets using an unsupervised domain Adversarial Network (2024)
Journal Article
Xie, Y., Jin, L., Zhu, C., Luo, W., & Wang, Q. (2024). Enhanced cross-domain lithology classification in imbalanced datasets using an unsupervised domain Adversarial Network. Engineering Applications of Artificial Intelligence, 139(Part B), Article 109668. https://doi.org/10.1016/j.engappai.2024.109668

Recent advancements in Artificial Intelligence (AI), particularly deep learning, have significantly improved lithology identification in reservoir exploration by leveraging micrographic rock imagery. Deep neural networks excel in feature extraction,... Read More about Enhanced cross-domain lithology classification in imbalanced datasets using an unsupervised domain Adversarial Network.

Premature mortality analysis of 52,000 deceased cats and dogs exposes socioeconomic disparities (2024)
Journal Article
Farrell, S., Anderson, K., Noble, P.-J. M., & Al Moubayed, N. (2024). Premature mortality analysis of 52,000 deceased cats and dogs exposes socioeconomic disparities. Scientific Reports, 14(1), Article 28763. https://doi.org/10.1038/s41598-024-77385-8

Monitoring mortality rates offers crucial insights into public health by uncovering the hidden impacts of diseases, identifying emerging trends, optimising resource allocation, and informing effective policy decisions. Here, we present a novel approa... Read More about Premature mortality analysis of 52,000 deceased cats and dogs exposes socioeconomic disparities.

A topic map based learning management system to facilitate meaningful grammar learning: the case of Japanese grammar learning (2024)
Journal Article
Wang, J., Wynn, A., Mendori, T., & Hwang, G.-J. (2024). A topic map based learning management system to facilitate meaningful grammar learning: the case of Japanese grammar learning. Smart Learning Environments, 11(1), Article 53. https://doi.org/10.1186/s40561-024-00338-1

This study investigates the effect of studying with topic maps provided by a self-developed language learning support system on (a) learning perception, (b) learning achievement and (c) variation in learning attitude and motivation, from the perspect... Read More about A topic map based learning management system to facilitate meaningful grammar learning: the case of Japanese grammar learning.

ExaGRyPE: Numerical general relativity solvers based upon the hyperbolic PDEs solver engine ExaHyPE (2024)
Journal Article
Zhang, H., Li, B., Weinzierl, T., & Barrera-Hinojosa, C. (2025). ExaGRyPE: Numerical general relativity solvers based upon the hyperbolic PDEs solver engine ExaHyPE. Computer Physics Communications, 307, Article 109435. https://doi.org/10.1016/j.cpc.2024.109435

ExaGRyPE describes a suite of solvers and solver ingredients for numerical relativity that are based upon ExaHyPE 2, the second generation of our Exascale Hyperbolic PDE Engine. Numerical relativity simulations are crucial in resolv... Read More about ExaGRyPE: Numerical general relativity solvers based upon the hyperbolic PDEs solver engine ExaHyPE.

GANzzle + + : Generative approaches for jigsaw puzzle solving as local to global assignment in latent spatial representations (2024)
Journal Article
Talon, D., Del Bue, A., & James, S. (2025). GANzzle + + : Generative approaches for jigsaw puzzle solving as local to global assignment in latent spatial representations. Pattern Recognition Letters, 187, 35-41. https://doi.org/10.1016/j.patrec.2024.11.010

Jigsaw puzzles are a popular and enjoyable pastime that humans can easily solve, even with many pieces. However, solving a jigsaw is a combinatorial problem, and the space of possible solutions is exponential in the number of pieces, intractable for... Read More about GANzzle + + : Generative approaches for jigsaw puzzle solving as local to global assignment in latent spatial representations.

Evidence Retrieval for Fact Verification using Multi-stage Reranking (2024)
Presentation / Conference Contribution
Malviya, S., & Katsigiannis, S. (2024, November). Evidence Retrieval for Fact Verification using Multi-stage Reranking. Presented at 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), Miami, FL, USA

Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum (2024)
Presentation / Conference Contribution
Dua, A., Singh Aujla, G., Jindal, A., & Sun, H. (2024, December). Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum. Presented at IEEE Global Communications Conference - Workshop on Next-Gen Healthcare Fusion (NgHF): AI-driven Secure Integrated Networks for Healthcare IoT Systems, Cape Town, South Africa

The increasing demand for machine learning (ML) technologies has led to a significant rise in energy consumption and environmental impact, particularly within the context of distributed computing environments like the Edge-Fog-Cloud Continuum. This p... Read More about Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum.

Toward a framework for Responsible AI in storytelling for nonprofit fundraising (2024)
Book Chapter
Herrero, M., & Concannon, S. (2024). Toward a framework for Responsible AI in storytelling for nonprofit fundraising. In G. Ugazio, & M. Maricic (Eds.), . Routledge. https://doi.org/10.4324/9781003468615-11

AI techniques offer novel and compelling possibilities for nonprofit fundraising (e.g., data science applications can provide a deeper understanding of audiences and donors, and generative methods can create more personalized and persuasive communica... Read More about Toward a framework for Responsible AI in storytelling for nonprofit fundraising.

Democratizing Uncertainty Quantification (2024)
Journal Article
Seelinger, L., Reinarz, A., Lykkegaard, M. B., Akers, R., Alghamdi, A. M., Aristoff, D., Bangerth, W., Bénézech, J., Diez, M., Frey, K., Jakeman, J. D., Jørgensen, J. S., Kim, K.-T., Kent, B. M., Martinelli, M., Parno, M., Pellegrini, R., Petra, N., Riis, N. A., Rosenfeld, K., …Scheichl, R. (2025). Democratizing Uncertainty Quantification. Journal of Computational Physics, 521(1), Article 113542. https://doi.org/10.1016/j.jcp.2024.113542

Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling... Read More about Democratizing Uncertainty Quantification.