A key feature of out-of-distribution (OOD) detection is to exploit a tra...
Hypothesis transfer learning (HTL) contrasts domain adaptation by allowi...
Out-of-distribution (OOD) detection is a rapidly growing field due to ne...
Deep learning methods have boosted the adoption of NLP systems in real-l...
Temporal point processes (TPP) are a natural tool for modeling event-bas...
When working with textual data, a natural application of disentangled
re...
The increasing automation in many areas of the Industry expressly demand...
A new metric to evaluate text generation based on deep
contextualized e...
Because it determines a center-outward ordering of observations in
ℝ^d w...
Data depth is a non parametric statistical tool that measures centrality...
Issued from Optimal Transport, the Wasserstein distance has gained impor...
In contrast to the empirical mean, the Median-of-Means (MoM) is an estim...
With the ubiquity of sensors in the IoT era, statistical observations ar...
For the purpose of monitoring the behavior of complex infrastructures (e...