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ChernovAndrei

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Show HN: Store and reuse your Claude Code plans

github.com
1 ポイント·投稿者 ChernovAndrei·4 か月前·0 コメント

Show HN: Python SDK – forecasting with foundation time-series and tabular models

github.com
43 ポイント·投稿者 ChernovAndrei·7 か月前·18 コメント

Show HN: UI front end to forecast with foundation time-series models

faim.it.com
1 ポイント·投稿者 ChernovAndrei·7 か月前·0 コメント

Show HN: MCP Server for Time-Series Forecasting

github.com
1 ポイント·投稿者 ChernovAndrei·8 か月前·1 コメント

Show HN: JavaScript SDK for zero-shot time-series forecasting (Chronos2, TiRex)

github.com
2 ポイント·投稿者 ChernovAndrei·8 か月前·0 コメント

Show HN: Serverless platform for inference of time-series foundation models

faim.it.com
1 ポイント·投稿者 ChernovAndrei·8 か月前·0 コメント

コメント

ChernovAndrei
·7 か月前·議論
There is no single answer, because there are multiple architectures for foundation time-series models, such as T5, decoder-only models, and state-space models (SSMs).

For Chronos-2 (the current state of the art in time-series modeling), the setup is almost identical to that of LLMs because it is based on the T5 architecture. The main difference is that, in time-series models, tokens correspond to subintervals in the real-valued (ℝ) space. You can check the details here: https://arxiv.org/pdf/2510.15821
ChernovAndrei
·7 か月前·議論
Limix outperforms tabpfn v2: https://arxiv.org/pdf/2509.03505