6 citations · 12 across the 3 of their papers we have counts for
4 papers
RealCause: Realistic Causal Inference Benchmarking
Brady Neal, Chin-Wei Huang, Sunand Raghupathi
There are many different causal effect estimators in causal inference. However, it is unclear how to choose between these estimators because there is no ground-truth for causal eff…
In Search of Robust Measures of Generalization
Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal +5
One of the principal scientific challenges in deep learning is explaining generalization, i.e., why the particular way the community now trains networks to achieve small training e…
On the Bias-Variance Tradeoff: Textbooks Need an Update
Brady Neal
The main goal of this thesis is to point out that the bias-variance tradeoff is not always true (e.g. in neural networks). We advocate for this lack of universality to be acknowled…
How well does your sampler really work?
Ryan Turner, Brady Neal
We present a new data-driven benchmark system to evaluate the performance of new MCMC samplers. Taking inspiration from the COCO benchmark in optimization, we view this task as hav…