175 citations · 248 across the 5 of their papers we have counts for
5 papers
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data
Siyuan Guo, Viktor Tóth, Bernhard Schölkopf +1
Constraint-based causal discovery methods leverage conditional independence tests to infer causal relationships in a wide variety of applications. Just as the majority of machine l…
Depth Without the Magic: Inductive Bias of Natural Gradient Descent
Anna Kerekes, Anna Mészáros, Ferenc Huszár
In gradient descent, changing how we parametrize the model can lead to drastically different optimization trajectories, giving rise to a surprising range of meaningful inductive bi…
Algorithmic Amplification of Politics on Twitter
Ferenc Huszár, Sofia Ira Ktena, Conor O'Brien +3
Content on Twitter's home timeline is selected and ordered by personalization algorithms. By consistently ranking certain content higher, these algorithms may amplify some messages…
Adaptive Bayesian Quantum Tomography
Ferenc Huszár, Neil M. T. Houlsby
In this letter we revisit the problem of optimal design of quantum tomographic experiments. In contrast to previous approaches where an optimal set of measurements is decided in ad…
A Kernel Approach to Tractable Bayesian Nonparametrics
Ferenc Huszár, Simon Lacoste-Julien
Inference in popular nonparametric Bayesian models typically relies on sampling or other approximations. This paper presents a general methodology for constructing novel tractable…