Discovery Science 2023 conference provides an open forum for intensive discussions and exchange of new ideas among researchers working in the area of Discovery Science. The conference focus is on the use of artificial intelligence methods in science. Its scope includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, and big data analytics, as well as their application in various domains.
Possible topics include, but are not limited to:
-Artificial intelligence (machine learning, knowledge representation and reasoning, natural language processing, statistical methods, etc.) applied to science -Machine learning: supervised learning (including ranking, multi-target prediction and structured prediction), unsupervised learning, semi-supervised learning, active learning, reinforcement learning, online learning, transfer learning, etc.
-Knowledge discovery and data mining
-AutoML, meta-learning, planning to learn -Machine learning and high-performance computing, grid and cloud computing -Literature-based discovery -Ontologies for science, including the representation and annotation of datasets and domain knowledge -Explainable AI, interpretability of machine learning and deep learning models -Process discovery and analysis -Computational creativity -Anomaly detection and outlier detection -Data streams, evolving data, change detection, concept drift, model maintenance -Network analysis -Time-series analysis -Learning from complex data -Graphs, networks, linked and relational data -Spatial, temporal and spatiotemporal data -Unstructured data, including textual and web data -Multimedia data -Data and knowledge visualization -Human-machine interaction for knowledge discovery and management -Evaluation of models and predictions in discovery setting -Machine learning and cybersecurity -Applications of the above techniques in scientific domains, such as -Physical sciences (e.g., materials sciences, particle physics) -Life sciences (e.g., systems biology/systems medicine) -Environmental sciences -Natural and social sciences
There will be a Best Student Paper Award in the value of 555 Eur sponsored by Springer.
Abstract submission (deadline): May 27, 2023 Full paper submission (deadline): Jun 3, 2023 Notification of acceptance: July 21, 2023 Camera ready version, author registration: August 6, 2023
-More Information at: https://ds2023.inesctec.pt/
- Porto Portugal
- 09/10/2023 12:00 am
- Visit website