Blair Bilodeau | DeepAI

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∙ 06/07/2023

Don't trust your eyes: on the (un)reliability of feature visualizations

How do neural networks extract patterns from pixels? Feature visualizati...

0 Robert Geirhos, et al. ∙

∙ 12/22/2022

Impossibility Theorems for Feature Attribution

Despite a sea of interpretability methods that can produce plausible exp...

3 Blair Bilodeau, et al. ∙

∙ 10/17/2022

On the Tightness of the Laplace Approximation for Statistical Inference

Laplace's method is used to approximate intractable integrals in a wide ...

0 Blair Bilodeau, et al. ∙

∙ 02/16/2022

Fitting Generalized Linear Mixed Models using Adaptive Quadrature

We describe how to approximate the intractable marginal likelihood that ...

0 Alex Stringer, et al. ∙

∙ 02/10/2022

Adaptively Exploiting d-Separators with Causal Bandits

Multi-armed bandit problems provide a framework to identify the optimal ...

0 Blair Bilodeau, et al. ∙

∙ 09/21/2021

Minimax Rates for Conditional Density Estimation via Empirical Entropy

We consider the task of estimating a conditional density using i.i.d. sa...

0 Blair Bilodeau, et al. ∙

∙ 02/12/2021

Stochastic Convergence Rates and Applications of Adaptive Quadrature in Bayesian Inference

We provide the first stochastic convergence rates for adaptive Gauss–Her...

0 Blair Bilodeau, et al. ∙

∙ 07/13/2020

Relaxing the I.I.D. Assumption: Adaptive Minimax Optimal Sequential Prediction with Expert Advice

We consider sequential prediction with expert advice when the data are g...

0 Blair Bilodeau, et al. ∙

∙ 07/02/2020

Improved Bounds on Minimax Regret under Logarithmic Loss via Self-Concordance

We consider the classical problem of sequential probability assignment u...

0 Blair Bilodeau, et al. ∙

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