Ruda Zhang | Gaussian Process Subspace Regression
Ruda Zhang (Duke University) walks us through "Gaussian Process Subspace Regression for Model Reduction" by Zhang, Mak, and Dunson.
To keep the topic interesting for both the early career & advanced audience we recap key points at a high level so that no one gets lost.
This episode involves a presentation, so you may prefer to watch the YouTube version here: https://youtu.be/IPtqUUG4XcY
Ruda's website: https://ruda.city/
The paper: https://arxiv.org/abs/2107.04668
Keith O’Rourke | The Logic of Statistics
Jack Fitzsimons | Evil Models: Hiding Malware in Neural Networks
Scott Cunningham | Causal Inference (The Mixtape)
Eric Daza | Important Ideas in Causal Inference
Wenting Cheng & Weidong Zhang | Advances in Biotech/Biopharma
Ruda Zhang | Math-Science Duality
Simon Mak | Integrating Science into Stats Models
Martin Goodson | Practical Data Science & The UK’s AI Roadmap
Jack Fitzsimons | Data Security, Privacy, & Artificial Intelligence
Chris Tosh | The piranha problem in statistics
Chris Holmes | AI, Digital Health, & The Alan Turing Institute
Philosophy of Data Science | Deborah Mayo | Revolutions, Reforms, and Severe Testing in Statistical Thinking
Charlotte Deane | Bioinformatics, Deepmind’s AlphaFold 2, and Llamas
Eric Schwitzgebel | Consciousness, Zombies, & First Person Data | Philosophy of Data Science
Starting a Statistics Consultancy | Janet Wittes
Philosophy of Data Science | Jingyi Jessica Li | Advancing Statistical Genomics
Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education
Jingyi Jessica Li | Statistical Hypothesis Testing vs Machine Learning Binary Classification
Gualtiero Piccinini | What Are First-Person Data? | Philosophy of Data Science
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