Kernel Single Proxy Control for Deterministic Confounding

at #AISTATS25

Proxy causal learning generally requires two proxy variables - a treatment and an outcome proxy. When is it possible to use just one?

arxiv.org/abs/2308.04585

Liyuan Xu

Credal Two-Sample Tests of Epistemic Uncertainty
at #AISTATS25

Compare credal sets: convex sets of prob measures where elements capture aleatoric uncertainty; set represents epistemic uncertainty.

arxiv.org/abs/2410.12921

@slchau.bsky.social Schrab @sejdino.bsky.social @krikamol.bsky.social

Are you interested in Invertible Convolution or Flow models?
I will be presenting our work 'Inverse-Flow' at #AISTATS25
Session 3, 5th may, 3-6 pm, Hall A-E 48.
#GenerativeModels , #ML, #phuket

Our paper, “Poisoning Bayesian Inference via Data Deletion and Replication,” has been accepted to #AISTATS25.

In it, we propose “posterior attraction problems”, a new family of challenges in Bayesian robustness.

Stay tuned for more.