121 citations · 416 across the 16 of their papers we have counts for
22 papers
Temporal Conductance and Bounds on the Voter Model for Dynamic Networks
Tatiana Rocha Avila, Holger Dell, John Lapinskas
The voter model is a classical stochastic process that models how opinions might spread through a network: at each step, every node lazily adopts the opinion of a random neighbour;…
Factored space models: Towards causality between levels of abstraction
Scott Garrabrant, Matthias Georg Mayer, Magdalena Wache +3
Causality plays an important role in understanding intelligent behavior, and there is a wealth of literature on mathematical models for causality, most of which is focused on causa…
Fairness Through Controlled (Un)Awareness in Node Embeddings
Dennis Vetter, Jasper Forth, Gemma Roig +1
Graph representation learning is central for the application of machine learning (ML) models to complex graphs, such as social networks. Ensuring `fair' representations is essentia…
Nearly optimal independence oracle algorithms for edge estimation in hypergraphs
Holger Dell, John Lapinskas, Kitty Meeks
We study a query model of computation in which an n-vertex k-hypergraph can be accessed only via its independence oracle or via its colourful independence oracle, and each oracle q…
Modular counting of subgraphs: Matchings, matching-splittable graphs, and paths
Radu Curticapean, Holger Dell, Thore Husfeldt
We systematically investigate the complexity of counting subgraph patterns modulo fixed integers. For example, it is known that the parity of the number of -matchings can be det…
Approximately counting and sampling small witnesses using a colourful decision oracle
Holger Dell, John Lapinskas, Kitty Meeks
In this paper, we design efficient algorithms to approximately count the number of edges of a given -hypergraph, and to sample an approximately uniform random edge. The hypergra…