Normalizing flow-based neural process for few-shot knowledge graph completion
Knowledge graphs (KGs), as a structured form of knowledge representation, have been
widely applied in the real world. Recently, few-shot knowledge graph completion (FKGC) …
widely applied in the real world. Recently, few-shot knowledge graph completion (FKGC) …
Towards few-shot inductive link prediction on knowledge graphs: A relational anonymous walk-guided neural process approach
Few-shot inductive link prediction on knowledge graphs (KGs) aims to predict missing links
for unseen entities with few-shot links observed. Previous methods are limited to …
for unseen entities with few-shot links observed. Previous methods are limited to …
Evidential conditional neural processes
Abstract The Conditional Neural Process (CNP) family of models offer a promising direction
to tackle few-shot problems by achieving better scalability and competitive predictive …
to tackle few-shot problems by achieving better scalability and competitive predictive …
Bridge the inference gaps of neural processes via expectation maximization
Q Wang, M Federici, H van Hoof - The Eleventh International …, 2023 - openreview.net
The neural process (NP) is a family of computationally efficient models for learning
distributions over functions. However, it suffers from under-fitting and shows suboptimal …
distributions over functions. However, it suffers from under-fitting and shows suboptimal …