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Invited Talks
- Grounding deep models with uncertainty quantification [Slides]
- Designing calibrated uncertainty estimators for deep models, DLCT (ML Collective) [Slides]
- Improving reliability and interpretability of AI models in clinical diagnosis, LLNL DSI AI in Healthcare Workshop [Slides]
- Building reliable and generalizable deep models using prediction calibration [Slides]
- Thoughts on building machine learning models with scientific data [Slides]
- Explaining real-word shifts and explaining under shifts [Slides]
- Understanding behavior of clinical models under domain shifts [Slides]
- Tutorial on unsupervised learning [Part 1] [Part 2] [Part 3]
- Teaching machines to be intelligent: Pitfalls, Challenges and Opportunities [Slides]
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