Guilherme Jardim Duarte
@guilhermejd1
PhD candidate (OID - @Wharton - @Penn). interests: causality, ML
ID: 37321213
03-05-2009 00:38:19
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Today I’m becoming a PhD—this time from Wharton (UPenn). I’m deeply grateful to everyone who supported me, especially my committee: Dean Knox, Jonathan Mummolo , Hamsa Bastani, and Eric Tchetgen Tchetgen.
Finally, a good modern book on causality for ML: causalai-book.net by Elias Bareinboim. This looks like a worthy successor to the ground breaking book by Judea Pearl which I read in grad school. (h/t Joshua Safyan for the ref).
In his job market paper, Christian Baehr examines how permanent oil revenue shortfalls reshape distributional conflicts in oil-dependent states and drive targeted institutional reforms to strengthen public goods provision, offering insight into how these states will respond to
In her book project, Heather Penatzer examines internationalized territories as a distinct form of alien rule. Dr. Penatzer was awarded the “Best Student Paper in International Law” at ISA 2024 and Princeton’s George Kateb teaching prize in 2024. She is currently a postdoctoral
![How should you use forecasts f:X->R^d to make decisions? It depends what properties they have. If they are fully calibrated (E[y | f(x) = p] = p), then you should be maximally agressive and act as if they are correct --- i.e. play argmax_a E_{o ~ f(x)}[u(a,o)]. On the other hand](https://pbs.twimg.com/media/G4h5eHOXUAAg32X.png "Aaron Roth (@aaroth) on Twitter photo How should you use forecasts f:X->R^d to make decisions? It depends what properties they have. If they are fully calibrated (E[y | f(x) = p] = p), then you should be maximally agressive and act as if they are correct --- i.e. play argmax_a E_{o ~ f(x)}[u(a,o)]. On the other hand")
