24 citations · 73 across the 16 of their papers we have counts for
3 papers · 1 filter
Beyond Mahalanobis-Based Scores for Textual OOD Detection
Pierre Colombo, Eduardo D. C. Gomes, Guillaume Staerman +2
Deep learning methods have boosted the adoption of NLP systems in real-life applications. However, they turn out to be vulnerable to distribution shifts over time which may cause s…
Learning Disentangled Textual Representations via Statistical Measures of Similarity
Pierre Colombo, Guillaume Staerman, Nathan Noiry +1
When working with textual data, a natural application of disentangled representations is fair classification where the goal is to make predictions without being biased (or influenc…
Functional Anomaly Detection: a Benchmark Study
Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi +3
The increasing automation in many areas of the Industry expressly demands to design efficient machine-learning solutions for the detection of abnormal events. With the ubiquitous d…