6 citations · 13 across the 5 of their papers we have counts for
5 papers
A Simple and Powerful Framework for Stable Dynamic Network Embedding
Ed Davis, Ian Gallagher, Daniel John Lawson +1
In this paper, we address the problem of dynamic network embedding, that is, representing the nodes of a dynamic network as evolving vectors within a low-dimensional space. While t…
Forecasting the 2016-2017 Central Apennines Earthquake Sequence with a Neural Point Process
Samuel Stockman, Daniel J. Lawson, Maximilian J. Werner
Point processes have been dominant in modeling the evolution of seismicity for decades, with the Epidemic Type Aftershock Sequence (ETAS) model being most popular. Recent advances…
Posterior predictive p-values and the convex order
Patrick Rubin-Delanchy, Daniel John Lawson
Posterior predictive p-values are a common approach to Bayesian model-checking. This article analyses their frequency behaviour, that is, their distribution when the parameters and…
A general decision framework for structuring computation using Data Directional Scaling to process massive similarity matrices
Daniel John Lawson, Niall M Adams
As datasets grow it becomes infeasible to process them completely with a desired model. For giant datasets, we frame the order in which computation is performed as a decision probl…
Apparent strength conceals instability in a model for the collapse of historical states
Daniel John Lawson, Neeraj Oak
An explanation for the political processes leading to the sudden collapse of empires and states would be useful for understanding both historical and contemporary political events.…