Representation Learning
Evaluation complete
MantisV2
A more lightweight Mantis encoder trained for stronger zero-shot time series representations.
Method overview
A more lightweight Mantis encoder trained for stronger zero-shot time series representations.
Evaluated configurations
LR
RF
ScaledLR
Classifier heads are grouped on this page under their shared pretrained model. They remain separate leaderboard entries because they represent different experimental configurations.
- Organization
- Huawei Noah’s Ark Lab · Université Paris Cité
- Parameters
- 4.19M backbone
- Checkpoint used
- MantisV2
- Input Type
- Univariate + multivariate time series
- Inference
- Frozen representation + fitted classifier
Reading this model's evaluation
The method catalog describes the pretrained model; leaderboard eligibility depends on the actual coverage of each experimental configuration. Catalog inclusion does not imply complete coverage of all 198 datasets.