Results 41 to 50 of about 275,882 (279)

Statistical Relational Learning with Formal Ontologies [PDF]

, 2009
We propose a learning approach for integrating formal knowledge into statistical inference by exploiting ontologies as a semantically rich and fully formal representation of prior knowledge. The logical constraints deduced from ontologies can be utilized to enhance and control the learning task by enforcing description logic satisfiability in a latent ...
Rettinger, Achim, Nickles, Matthias, Tresp, Volker   +2 more
openaire   +2 more sources

Statistical learning creates novel object associations via transitive relations [PDF]

Journal of Vision, 2016
A remarkable ability of the cognitive system is to make novel inferences on the basis of prior experiences. What mechanism supports such inferences? We propose that statistical learning is a process through which transitive inferences of new associations are made between objects that have never been directly associated.
Yu Luo, Jiaying Zhao
openaire   +3 more sources

Improving Data Quality by Leveraging Statistical Relational Learning [PDF]

, 2016
Digitally collected data su ↵ ers from many data quality issues, such as duplicate, incorrect, or incomplete data. A common approach for counteracting these issues is to formulate a set of data cleaning rules to identify and repair incorrect ...
Akbik, A, Kaul, Manohar, Markl, V, Rabl, T, Visengeriyeva, L   +4 more
core   +2 more sources

Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany

Scientific Reports, 2022
During 2020, the infection rate of COVID-19 has been investigated by many scholars from different research fields. In this context, reliable and interpretable forecasts of disease incidents are a vital tool for policymakers to manage healthcare resources.
Cornelius Fritz, Emilio Dorigatti, David Rügamer   +2 more
doaj   +1 more source

Rapid Proteome‐Wide Discovery of Protein–Protein Interactions With ppIRIS

Advanced Science, EarlyView.
ppIRIS is a lightweight deep learning framework for proteome‐wide protein–protein interaction prediction directly from sequence. By fusing evolutionary and structural embeddings with a regularized Siamese architecture, ppIRIS achieves state‐of‐the‐art accuracy across species, enables minute‐scale screening, and reveals biologically validated bacterial ...
Luiz Felipe Piochi, Di Tang, Johan Malmström, Yasaman Karami, Hamed Khakzad   +4 more
wiley   +1 more source

Statistical relational learning for workflow mining

Intelligent Data Analysis, 2016
The management of business processes can support efficiency improvements in organizations. One of the most interesting problems is the mining and representation of process models in a declarative language. Various recently proposed knowledge-based languages showed advantages over graph-based procedural notations.
BELLODI, Elena, RIGUZZI, Fabrizio, LAMMA, Evelina   +2 more
openaire   +2 more sources

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

A Novel Hybrid Temporal Fusion Transformer Graph Neural Network Model for Stock Market Prediction

AppliedMath
Forecasting stock prices remains a central challenge in financial modelling, as markets are influenced by market sentiment, firm-level fundamentals and complex interactions between macroeconomic and microeconomic factors, for example.
Sebastian Thomas Lynch, Parisa Derakhshan, Stephen Lynch   +2 more
doaj   +1 more source

Composition of Sentence Embeddings: Lessons from Statistical Relational Learning [PDF]

Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), 2019
Camera-ready for *SEM ...
Sileo, Damien, Van-De-Cruys, Tim, Pradel, Camille, Muller, Philippe   +3 more
openaire   +2 more sources

Stable Diffusion Models Reveal a Persisting Human–AI Gap in Visual Creativity

Advanced Science, EarlyView.
This study examines visual creativity in humans and generative AI using the TCIA framework. Human artists outperform AI overall, yet structured human guidance substantially improves AI outputs and evaluations. Findings reveal that alignment with human creativity depends critically on contextual framing, highlighting both the promise and current ...
Silvia Rondini, Claudia Alvarez‐Martin, Paula Angermair‐Barkai, Olivier Penacchio, Marc Paz, Matthew Pelowski, Dan Dediu, Antoni Rodriguez‐Fornells, Xim Cerda‐Company   +8 more
wiley   +1 more source