506 citations
- Centre National de la Recherche ScientifiqueFR44 papers
- University of EdinburghGB44 papers
- European Southern ObservatoryCL39 papers
- Royal ObservatoryGB37 papers
- Herzberg Institute of AstrophysicsCA36 papers
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- Institute of Astronomy and Astrophysics, Academia SinicaTW24 papers
- Leiden UniversityNL24 papers
16 papers · 1 filter
Machine Learning in Fish Farming
Fearghal O'Donncha, Nikos Papandroulakis, Jennie Korus +10
This chapter explores how machine learning (ML) is transforming aquaculture, with a particular focus on enhancing decision-making processes and improving operational efficiency. Th…
Goal-Conditioned Reinforcement Learning for Data-Driven Maritime Navigation
Vaishnav Vaidheeswaran, Dilith Jayakody, Samruddhi Mulay +3
Routing vessels through narrow and dynamic waterways is challenging due to changing environmental conditions and operational constraints. Existing vessel-routing studies typically…
Addressing Correlated Latent Exogenous Variables in Debiased Recommender Systems
Shuqiang Zhang, Yuchao Zhang, Jinkun Chen +1
Recommendation systems (RS) aim to provide personalized content, but they face a challenge in unbiased learning due to selection bias, where users only interact with items they pre…
Physics-Informed Neural Networks for Vessel Trajectory Prediction: Learning Time-Discretized Kinematic Dynamics via Finite Differences
Md Mahbub Alam, Amilcar Soares, José F. Rodrigues-Jr +1
Accurate vessel trajectory prediction is crucial for navigational safety, route optimization, traffic management, search and rescue operations, and autonomous navigation. Tradition…
Label-free Monitoring of Self-Supervised Learning Progress
Isaac Xu, Scott Lowe, Thomas Trappenberg
Self-supervised learning (SSL) is an effective method for exploiting unlabelled data to learn a high-level embedding space that can be used for various downstream tasks. However, e…
RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms
Luis Roque, Carlos Soares, Luís Torgo
We introduce the Robustness of Hierarchically Organized Time Series (RHiOTS) framework, designed to assess the robustness of hierarchical time series forecasting models and algorit…