Using TiCT for time series classification
A synthetically pretrained time series in-context classifier with scalable label encoding.
In this benchmark, TiCT is evaluated using training-free in-context classification. Checkpoint information: No standalone checkpoint link found. Check the results below for the settings and dataset scopes with published scores.
Evaluated configurations
Classifier heads are grouped under their shared pretrained model here. They remain separate leaderboard entries because they are different experimental configurations.
- Organization
- Visa Research
- Parameters
- 47M (TiCT-Large, ResNet)
- Checkpoint used
- No standalone checkpoint link found
- Input Type
- Univariate time series
- Inference
- Training-free in-context classification
TiCT classification benchmark results
Compare accuracy and average rank only within the same evaluation setting and dataset scope. Standard uses the official training splits; 5-shot and 10-shot use different budget-feasible subsets. Rank and average rank include other models in the full comparison set. Scores are not averaged across configurations.
For comparisons with other backbones, open the foundation model classification leaderboard and use the same setting and scope. The few-shot evaluation protocol explains the label budgets.
Standard · Univariate
Comparison set: 19 configurations
This Standard time series classification comparison reports 1 TiCT configuration for the univariate dataset scope. Each row shows its own coverage.
The highest reported average accuracy among this model's configurations in this setting is 79.17%, reported by TiCT with coverage 128 / 128. This configuration ranks 4 of 19 in this comparison set. The result describes this configuration and setting, rather than every possible use of the pretrained model.
| Configuration | Univariate Rank | Univariate Accuracy (%) | Avg. Rank | Coverage |
|---|---|---|---|---|
| TiCT | 4 | 79.17 | 6.68 | 128 / 128 |
TiCT paper, code and checkpoint
- PaperOpen official resource
- CodeOpen official resource
- CheckpointNo standalone checkpoint link found
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.