Fergus Imrie

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 37

Top Topics

Machine Learning

Differential Equations

Top Venues

Publications

Dennis Frauen, Fergus Imrie, Alicia Curth, Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar
A Neural Framework for Generalized Causal Sensitivity Analysis. ICLR (2024)
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI. ICLR (2024)
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI. CoRR (2024)
Nabeel Seedat, Nicolas Huynh, Fergus Imrie, Mihaela van der Schaar
You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling. CoRR (2024)
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Navigating Data-Centric Artificial Intelligence With DC-Check: Advances, Challenges, and Opportunities. IEEE Trans. Artif. Intell. 5 (6) (2024)
Fergus Imrie, Stefan Denner, Lucas S. Brunschwig, Klaus H. Maier-Hein, Mihaela van der Schaar
Automated Ensemble Multimodal Machine Learning for Healthcare. CoRR (2024)
Boris van Breugel, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data. NeurIPS (2023)
Maranga Mokaya, Fergus Imrie, Willem P. van Hoorn, Aleksandra Kalisz, Anthony R. Bradley, Charlotte M. Deane
Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning. Nat. Mac. Intell. 5 (4) (2023)
Fergus Imrie, Robert Davis, Mihaela van der Schaar
Multiple stakeholders drive diverse interpretability requirements for machine learning in healthcare. Nat. Mac. Intell. 5 (8) (2023)
Boris van Breugel, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data. CoRR (2023)
Fergus Imrie, Paulius Rauba, Mihaela van der Schaar
Redefining Digital Health Interfaces with Large Language Models. CoRR (2023)
Alexander Norcliffe, Bogdan Cebere, Fergus Imrie, Pietro Liè, Mihaela van der Schaar
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis. AISTATS (2023)
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Fergus Imrie, Mihaela van der Schaar
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization. ICLR (2023)
Jeroen Berrevoets, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Differentiable and Transportable Structure Learning. ICML (2023)
Alexander Norcliffe, Bogdan Cebere, Fergus Imrie, Pietro Liò, Mihaela van der Schaar
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis. CoRR (2023)
Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar
Improving Adaptive Conformal Prediction Using Self-Supervised Learning. CoRR (2023)
Eleonora Giunchiglia, Fergus Imrie, Mihaela van der Schaar, Thomas Lukasiewicz
Machine Learning with Requirements: a Manifesto. CoRR (2023)
Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar
To Impute or not to Impute? Missing Data in Treatment Effect Estimation. AISTATS (2023)
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Fergus Imrie, Mihaela van der Schaar
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization. CoRR (2023)
Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar
Improving Adaptive Conformal Prediction Using Self-Supervised Learning. AISTATS (2023)
Dennis Frauen, Fergus Imrie, Alicia Curth, Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar
A Neural Framework for Generalized Causal Sensitivity Analysis. CoRR (2023)
Fergus Imrie, Alexander Norcliffe, Pietro Lió, Mihaela van der Schaar
Composite Feature Selection Using Deep Ensembles. NeurIPS (2022)
Jeroen Berrevoets, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
Differentiable and Transportable Structure Learning. CoRR (2022)
Changhee Lee, Fergus Imrie, Mihaela van der Schaar
Self-Supervision Enhanced Feature Selection with Correlated Gates. ICLR (2022)
Thomas E. Hadfield, Fergus Imrie, Andy Merritt, Kristian Birchall, Charlotte M. Deane
Incorporating Target-Specific Pharmacophoric Information into Deep Generative Models for Fragment Elaboration. J. Chem. Inf. Model. 62 (10) (2022)
Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. CoRR (2022)
Fergus Imrie, Bogdan Cebere, Eoin F. McKinney, Mihaela van der Schaar
AutoPrognosis 2.0: Democratizing Diagnostic and Prognostic Modeling in Healthcare with Automated Machine Learning. CoRR (2022)
Fergus Imrie, Alexander Norcliffe, Pietro Liò, Mihaela van der Schaar
Composite Feature Selection using Deep Ensembles. CoRR (2022)
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems. CoRR (2022)
Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar
To Impute or not to Impute? - Missing Data in Treatment Effect Estimation. CoRR (2022)
Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. ICML (2022)
Jonathan Crabbé, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar
Explaining Latent Representations with a Corpus of Examples. NeurIPS (2021)
Yuchao Qin, Fergus Imrie, Alihan Hüyük, Daniel Jarrett, Alexander Gimson, Mihaela van der Schaar
Closing the loop in medical decision support by understanding clinical decision-making: A case study on organ transplantation. NeurIPS (2021)
Jonathan Crabbé, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar
Explaining Latent Representations with a Corpus of Examples. CoRR (2021)
Fergus Imrie, Anthony R. Bradley, Charlotte M. Deane
Generating property-matched decoy molecules using deep learning. Bioinform. 37 (15) (2021)
Fergus Imrie, Anthony R. Bradley, Mihaela van der Schaar, Charlotte M. Deane
Deep Generative Models for 3D Linker Design. J. Chem. Inf. Model. 60 (4) (2020)
Fergus Imrie, Anthony R. Bradley, Mihaela van der Schaar, Charlotte M. Deane
Protein Family-Specific Models Using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data. J. Chem. Inf. Model. 58 (11) (2018)