59 citations · 72 across the 3 of their papers we have counts for
9 papers
Simulation-Based Inference for Global Health Decisions
Christian Schroeder de Witt, Bradley Gram-Hansen, Nantas Nardelli +8
The COVID-19 pandemic has highlighted the importance of in-silico epidemiological modelling in predicting the dynamics of infectious diseases to inform health policy and decision m…
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Atılım Güneş Baydin, Lei Shao, Wahid Bhimji +14
Probabilistic programming languages (PPLs) are receiving widespread attention for performing Bayesian inference in complex generative models. However, applications to science remai…
Hijacking Malaria Simulators with Probabilistic Programming
Bradley Gram-Hansen, Christian Schröder de Witt, Tom Rainforth +3
Epidemiology simulations have become a fundamental tool in the fight against the epidemics of various infectious diseases like AIDS and malaria. However, the complicated and stocha…
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models
Yuan Zhou, Bradley J. Gram-Hansen, Tobias Kohn +3
We develop a new Low-level, First-order Probabilistic Programming Language (LF-PPL) suited for models containing a mix of continuous, discrete, and/or piecewise-continuous variable…
Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral Data
Bradley Gram-Hansen, Patrick Helber, Indhu Varatharajan +4
Informal settlements are home to the most socially and economically vulnerable people on the planet. In order to deliver effective economic and social aid, non-government organizat…
Generating Material Maps to Map Informal Settlements
Patrick Helber, Bradley Gram-Hansen, Indhu Varatharajan +4
Detecting and mapping informal settlements encompasses several of the United Nations sustainable development goals. This is because informal settlements are home to the most social…