15.1k citations · 36.9k across the 152 of their papers we have counts for
4 papers · 2 filters
Combining Interventional and Observational Data Using Causal Reductions
Maximilian Ilse, Patrick Forré, Max Welling +1
Unobserved confounding is one of the main challenges when estimating causal effects. We propose a causal reduction method that, given a causal model, replaces an arbitrary number o…
Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel
Changyong Oh, Roberto Bondesan, Efstratios Gavves +1
In this work we propose a batch Bayesian optimization method for combinatorial problems on permutations, which is well suited for expensive-to-evaluate objectives. We first introdu…
Mixed Variable Bayesian Optimization with Frequency Modulated Kernels
Changyong Oh, Efstratios Gavves, Max Welling
The sample efficiency of Bayesian optimization(BO) is often boosted by Gaussian Process(GP) surrogate models. However, on mixed variable spaces, surrogate models other than GPs are…
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini +2
Generative flows and diffusion models have been predominantly trained on ordinal data, for example natural images. This paper introduces two extensions of flows and diffusion for c…