3/ TiViT: Time Series Representations for Classification Lie Hidden in Pretrained Vision Transformers @simonroschmann.bsky.social , @qbouniot.bsky.social , Vasilii Feofanov, Ievgen Redko, @zeynepakata.bsky.social

Time Series Representations for Classification Lie Hidden in Pretrained Vision Transformers

Time series classification is a fundamental task in healthcare and industry, yet the development of time series foundation models (TSFMs) remains limited by the scarcity of publicly available time ser...

arxiv.org

Excited to share that our paper "SOTAlign: Semi-Supervised Alignment of Unimodal Vision and Language Models via Optimal Transport" was accepted at ICML. 📄 Paper: arxiv.org/abs/2602.23353 💻 Code: github.com/ExplainableM...

Happy to share that we have 8 papers accepted to #ICML2026! 🎉 Most of the authors will be traveling to Seoul, Korea 🇰🇷 — feel free to reach out and chat with them if you’re interested in the work. See the full thread below for our papers 👇

How can we circumvent data scarcity in the time series domain? We propose to leverage pretrained ViTs (e.g., CLIP, DINOv2) for time series classification and outperform time series foundation models (TSFMs). 📄 Preprint: arxiv.org/abs/2506.08641 💻 Code: github.com/ExplainableM...