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Achievement: StarstruckAchievement: QuickdrawAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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riccardocadei/README.md

Hello World 🌍,

I am Riccardo 🇮🇹, an enthusiastic Ph.D. Student at Causal Learning and Artificial Intelligence Lab (ISTA) advised by Francesco Locatello and co-advised by Cordelia Schmid. Through my research, I aim to revisit general representation learning objectives when interested in causal downstream tasks (e.g., Treatment Effect Estimation) in order to (i) improve experiments' efficiency and (ii) provide trustworthy guarantees to AI-powered scientific discovery. Currently testing several applications in experimental ecology, and even more interested in applications in healthcare.

Here you can find a collection of different packages, challenges and problems regarding:

  • Machine Learning 📈,
  • Optimization 🎯,
  • Statistics 📊,
  • Causal Inference ⁉️,

that I have solved and implemented during the last few years and I can share publicly 🔓.

For a ordered archive of these projects see: MY PORTFOLIO 📁 and don't hesitate to reach out at [email protected] 📫 for any constructive discussion.

Enjoy the reading! 📖

Pinned Loading

  1. vita-epfl/causalmotion vita-epfl/causalmotion Public

    [CVPR22] Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective

    Python 73 11

  2. photovoltaic-detection photovoltaic-detection Public

    Detecting available rooftop area from satellite images to install photovoltaic panels - LESO-PB Lab @ EPFL

    Jupyter Notebook 36 12

  3. NSAPH-Software/CRE NSAPH-Software/CRE Public

    Forked from kwonsang/CRE

    The Causal Rule Ensemble Method

    R 13 5

  4. Higgs-Boson-Challange-2020-EPFL Higgs-Boson-Challange-2020-EPFL Public

    A classification problem on a big physical dataset simulated by the ATLAS experiment from CERN - @ EPFL

    Jupyter Notebook 7 2

  5. Robust-Journey-Planning Robust-Journey-Planning Public

    Robust and Efficient Journey Planning for Switzerland - @ EPFL

    Jupyter Notebook 3 1

  6. fbargaglistoffi/BCF-IV fbargaglistoffi/BCF-IV Public

    Package for heterogeneous causal effects in the presence of imperfect compliance (e.g., instrumental variables, fuzzy regression discontinuity designs)

    R 15 4