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Learning to learn
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Learning to learn
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Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: QuickdrawAchievement: StarstruckAchievement: YOLOAchievement: Arctic Code Vault Contributor

Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: QuickdrawAchievement: StarstruckAchievement: YOLOAchievement: Arctic Code Vault Contributor

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@CederGroupHub @COVID-19-Text-Mining

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idocx/README.md
idocx's Github Stats

Yuxing believes firmly in the saying "With four parameters I can fit an elephant, and with five I can make him wiggle his trunk" by Enrico Fermi. [1] So, he devotes his entire though short research career to tuning five hypermeters of a model and is convinced that he will finally make it outperform any SOTA models like GPT-3 and AlphaFold 2.

Yuxing is not a computer scientist, a physicist or a chemist, but a HYPERPARAMETER TUNING SCIENTIST. "That makes a lot of difference. Hyperparameter tuning is the technique that changes our life, especially before pulishing a paper.", he said.

[1] Dyson, F. A meeting with Enrico Fermi. Nature 427, 297 (2004).

📊 Weekly development time

From: 01 March 2026 - To: 08 March 2026

TeX            5 hrs 2 mins          ███████████████████▒░░░░░   77.65 %
Python         58 mins               ███▓░░░░░░░░░░░░░░░░░░░░░   15.09 %
HTML           13 mins               █░░░░░░░░░░░░░░░░░░░░░░░░   03.53 %
Markdown       4 mins                ▒░░░░░░░░░░░░░░░░░░░░░░░░   01.05 %
BibTeX         3 mins                ▒░░░░░░░░░░░░░░░░░░░░░░░░   00.85 %

Visitor Badge

Pinned Loading

  1. Atom2Vec Atom2Vec Public

    Atom2Vec: a simple way to describe atoms for machine learning

    Python 37 9

  2. CederGroupHub/alab_control CederGroupHub/alab_control Public

    Python 9 3

  3. CederGroupHub/alabos CederGroupHub/alabos Public

    AlabOS: Managing the workflows in the Autonomous lab

    Python 49 10

  4. CederGroupHub/dara CederGroupHub/dara Public

    DARA: Data-driven Automated Rietveld Analysis for powder XRD phase search and refinement

    Python 40 10