71 citations · 92 across the 8 of their papers we have counts for
8 papers
An AI-powered Tool for Central Bank Business Liaisons: Quantitative Indicators and On-demand Insights from Firms
Nicholas Gray, Finn Lattimore, Kate McLoughlin +1
In a world of increasing policy uncertainty, central banks are relying more on soft information sources to complement traditional economic statistics and model-based forecasts. One…
The Economic Effect of Gaining a New Qualification Later in Life
Finn Lattimore, Daniel M. Steinberg, Anna Zhu
Pursuing educational qualifications later in life is an increasingly common phenomenon within OECD countries since technological change and automation continues to drive the evolut…
Fast Fair Regression via Efficient Approximations of Mutual Information
Daniel Steinberg, Alistair Reid, Simon O'Callaghan +3
Most work in algorithmic fairness to date has focused on discrete outcomes, such as deciding whether to grant someone a loan or not. In these classification settings, group fairnes…
Causal inference with Bayes rule
Finnian Lattimore, David Rohde
The concept of causality has a controversial history. The question of whether it is possible to represent and address causal problems with probability theory, or if fundamentally n…
Replacing the do-calculus with Bayes rule
Finnian Lattimore, David Rohde
The concept of causality has a controversial history. The question of whether it is possible to represent and address causal problems with probability theory, or if fundamentally n…
A Primer on Causal Analysis
Finnian Lattimore, Cheng Soon Ong
We provide a conceptual map to navigate causal analysis problems. Focusing on the case of discrete random variables, we consider the case of causal effect estimation from observati…
Causal Bandits: Learning Good Interventions via Causal Inference
Finnian Lattimore, Tor Lattimore, Mark D. Reid
We study the problem of using causal models to improve the rate at which good interventions can be learned online in a stochastic environment. Our formalism combines multi-arm band…
The Crossover Process: Learnability and Data Protection from Inference Attacks
Richard Nock, Giorgio Patrini, Finnian Lattimore +1
It is usual to consider data protection and learnability as conflicting objectives. This is not always the case: we show how to jointly control inference --- seen as the attack ---…