99 citations · 157 across the 39 of their papers we have counts for
Showing 2022 · stat.MLShow all
3 papers · 2 filters
stat.ML2022★ 1 cited
Learning Linear Non-Gaussian Polytree Models
Daniele Tramontano, Anthea Monod, Mathias Drton
In the context of graphical causal discovery, we adapt the versatile framework of linear non-Gaussian acyclic models (LiNGAMs) to propose new algorithms to efficiently learn graphs…
stat.ML2022
Rewiring Networks for Graph Neural Network Training Using Discrete Geometry
Jakub Bober, Anthea Monod, Emil Saucan +1
Information over-squashing is a phenomenon of inefficient information propagation between distant nodes on networks. It is an important problem that is known to significantly impac…
stat.ML2022★ 4 cited
Approximating Persistent Homology for Large Datasets
Yueqi Cao, Anthea Monod
Persistent homology is an important methodology in topological data analysis which adapts theory from algebraic topology to data settings. Computing persistent homology produces pe…