Qlogice: Quantum logic empowered embedding for knowledge graph completion
Abstract Knowledge graph completion (KGC) is an important technique for implicitly
identifying missing entities or relations in knowledge graphs (KGs) that are employed in …
identifying missing entities or relations in knowledge graphs (KGs) that are employed in …
Deep Learning Models with Stratification-based Loss Function on Domain Knowledge-based Time series Data: Hypotension Prediction
H Jeong, J Kim, J Jeong, H Kim - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Intraoperative hypotension (IOH) negatively affects the prognosis after surgery. Therefore, in
recent years, various studies for IOH prediction based on bio-signal data have been carried …
recent years, various studies for IOH prediction based on bio-signal data have been carried …
Contrastive learning in neural tensor networks using asymmetric examples
Neuro-Symbolic models combine the best of two worlds, knowledge representation
capabilities of symbolic models and representation learning power of deep networks. In this …
capabilities of symbolic models and representation learning power of deep networks. In this …
[LIVRE][B] Advances in Improving Scalability and Accuracy of MLNS Using Symmetries
MM Islam - 2020 - search.proquest.com
Abstract Markov Logic Networks (MLNs) combine first-order logic with probabilistic graphical
models and are therefore capable of encoding complex domain knowledge. However …
models and are therefore capable of encoding complex domain knowledge. However …