Jonathan G. Richens

According to our database, Jonathan G. Richens authored at least 7 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Leveraging Directed Causal Discovery to Detect Latent Common Causes in Cause-Effect Pairs.

Ciarán M. Gilligan-Lee, Christopher Hart, Jonathan G. Richens, Saurabh Johri

IEEE Trans. Neural Networks Learn. Syst., April, 2024

2022

First do no harm: counterfactual objective functions for safe & ethical AI.

Jonathan G. Richens, Rory Beard, Daniel H. Thompson

CoRR, 2022

Counterfactual harm.

Jonathan G. Richens, Rory Beard, Daniel H. Thompson

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020

Learning medical triage from clinicians using Deep Q-Learning.

Albert Buchard, Baptiste Bouvier, Giulia Prando, Rory Beard, Michail Livieratos, Dan Busbridge, Daniel H. Thompson, Jonathan G. Richens, Yuanzhao Zhang, Adam Baker, Yura Perov, Kostis Gourgoulias, Saurabh Johri

CoRR, 2020

2019

Leveraging directed causal discovery to detect latent common causes.

Ciarán M. Lee, Christopher Hart, Jonathan G. Richens, Saurabh Johri

CoRR, 2019

Counterfactual diagnosis.

Jonathan G. Richens, Ciarán M. Lee, Saurabh Johri

CoRR, 2019

MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming.

Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens, Ciarán M. Lee, Adam Baker, Saurabh Johri

Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019