Jonathan G. Richens

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 8

Top Topics

Conditional Independence

Causal Reasoning

Importance Sampling

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

Publications

Ciarán M. Gilligan-Lee, Christopher Hart, Jonathan G. Richens, Saurabh Johri
Leveraging Directed Causal Discovery to Detect Latent Common Causes in Cause-Effect Pairs. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Jonathan G. Richens, Rory Beard, Daniel H. Thompson
Counterfactual harm. NeurIPS (2022)
Jonathan G. Richens, Rory Beard, Daniel H. Thompson
First do no harm: counterfactual objective functions for safe & ethical AI. CoRR (2022)
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
Learning medical triage from clinicians using Deep Q-Learning. CoRR (2020)
Jonathan G. Richens, Ciarán M. Lee, Saurabh Johri
Counterfactual diagnosis. CoRR (2019)
Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens, Ciarán M. Lee, Adam Baker, Saurabh Johri
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming. AABI (2019)
Ciarán M. Lee, Christopher Hart, Jonathan G. Richens, Saurabh Johri
Leveraging directed causal discovery to detect latent common causes. CoRR (2019)
Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens, Ciarán M. Lee, Adam Baker, Saurabh Johri
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming. CoRR (2019)