2 citations · 2 across the 4 of their papers we have counts for
3 papers · 1 filter
Feature Engineering for Agents: An Adaptive Cognitive Architecture for Interpretable ML Monitoring
Gusseppe Bravo-Rocca, Peini Liu, Jordi Guitart +3
Monitoring Machine Learning (ML) models in production environments is crucial, yet traditional approaches often yield verbose, low-interpretability outputs that hinder effective de…
TADIL: Task-Agnostic Domain-Incremental Learning through Task-ID Inference using Transformer Nearest-Centroid Embeddings
Gusseppe Bravo-Rocca, Peini Liu, Jordi Guitart +2
Machine Learning (ML) models struggle with data that changes over time or across domains due to factors such as noise, occlusion, illumination, or frequency, unlike humans who can…
Scanflow: A multi-graph framework for Machine Learning workflow management, supervision, and debugging
Gusseppe Bravo-Rocca, Peini Liu, Jordi Guitart +4
Machine Learning (ML) is more than just training models, the whole workflow must be considered. Once deployed, a ML model needs to be watched and constantly supervised and debugged…