2 citations · 2 across the 3 of their papers we have counts for
4 papers
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…
Fine-Grained Scheduling for Containerized HPC Workloads in Kubernetes Clusters
Peini Liu, Jordi Guitart
Containerization technology offers lightweight OS-level virtualization, and enables portability, reproducibility, and flexibility by packing applications with low performance overh…
Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation
Gusseppe Bravo-Rocca, Peini Liu, Jordi Guitart +3
Increasing a ML model accuracy is not enough, we must also increase its trustworthiness. This is an important step for building resilient AI systems for safety-critical application…
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…