1 citations · 1 across the 3 of their papers we have counts for
4 papers
Revisiting Catastrophic Forgetting in Continual Knowledge Graph Embedding
Gerard Pons, Carlos Escolano, Besim Bilalli +1
Knowledge Graph Embeddings (KGEs) support a wide range of downstream tasks over Knowledge Graphs (KGs). In practice, KGs evolve as new entities and facts are added, motivating Cont…
Improving Continual Learning of Knowledge Graph Embeddings via Informed Initialization
Gerard Pons, Besim Bilalli, Anna Queralt
Many Knowledege Graphs (KGs) are frequently updated, forcing their Knowledge Graph Embeddings (KGEs) to adapt to these changes. To address this problem, continual learning techniqu…
Towards Continuous Experiment-driven MLOps
Keerthiga Rajenthiram, Milad Abdullah, Ilias Gerostathopoulos +5
Despite advancements in MLOps and AutoML, ML development still remains challenging for data scientists. First, there is poor support for and limited control over optimizing and evo…
Capturing and Anticipating User Intents in Data Analytics via Knowledge Graphs
Gerard Pons, Besim Bilalli, Anna Queralt
In today's data-driven world, the ability to extract meaningful information from data is becoming essential for businesses, organizations and researchers alike. For that purpose, a…