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Fergus Imrie
Fergus Imrie
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα ucla.edu - Αρχική σελίδα
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Deep generative models for 3d linker design
F Imrie, AR Bradley, M van der Schaar, CM Deane
Journal of chemical information and modeling 60 (4), 1983-1995, 2020
1742020
Protein family-specific models using deep neural networks and transfer learning improve virtual screening and highlight the need for more data
F Imrie, AR Bradley, M van der Schaar, CM Deane
Journal of chemical information and modeling 58 (11), 2319-2330, 2018
1262018
Deep Generative Design with 3D Pharmacophoric Constraints
F Imrie, TE Hadfield, AR Bradley, CM Deane
Chemical Science 12, 14577-14589, 2021
572021
Generating property-matched decoy molecules using deep learning
F Imrie, AR Bradley, CM Deane
Bioinformatics 37 (15), 2134-2141, 2021
442021
Explaining Latent Representations with a Corpus of Examples
J Crabbé, Z Qian, F Imrie, M van der Schaar
Thirty-Fifth Conference on Neural Information Processing Systems, 2021
372021
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations
N Seedat*, F Imrie*, A Bellot, Z Qian, M van der Schaar
International Conference on Machine Learning 39, 2022
312022
AutoPrognosis 2.0: Democratizing diagnostic and prognostic modeling in healthcare with automated machine learning
F Imrie, B Cebere, EF McKinney, M van der Schaar
PLOS Digital Health 2 (6), e0000276, 2023
182023
Self-Supervision Enhanced Feature Selection with Correlated Gates
C Lee*, F Imrie*, M van der Schaar
International Conference on Learning Representations, 2022
162022
To Impute or not to Impute?--Missing Data in Treatment Effect Estimation
J Berrevoets, F Imrie, T Kyono, J Jordon, M van der Schaar
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
152023
Incorporating target-specific pharmacophoric information into deep generative models for fragment elaboration
TE Hadfield, F Imrie, A Merritt, K Birchall, CM Deane
Journal of chemical information and modeling 62 (10), 2280-2292, 2022
142022
Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning
M Mokaya, F Imrie, WP van Hoorn, A Kalisz, AR Bradley, CM Deane
Nature Machine Intelligence 5 (4), 386-394, 2023
132023
Navigating Data-Centric Artificial Intelligence with DC-Check: Advances, Challenges, and Opportunities
N Seedat, F Imrie, M van der Schaar
IEEE Transactions on Artificial Intelligence, 2023
12*2023
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization
A Jeffares*, T Liu*, J Crabbé, F Imrie, M van der Schaar
The Eleventh International Conference on Learning Representations, 2023
102023
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis
A Norcliffe*, B Cebere*, F Imrie, P Lio, M van der Schaar
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
72023
Composite Feature Selection using Deep Ensembles
F Imrie*, A Norcliffe*, P Lio, M van der Schaar
Advances in Neural Information Processing Systems 35, 2022
72022
Multiple stakeholders drive diverse interpretability requirements for machine learning in healthcare
F Imrie, R Davis, M van der Schaar
Nature Machine Intelligence 5 (8), 824-829, 2023
52023
Machine Learning with Requirements: a Manifesto
E Giunchiglia, F Imrie, M van der Schaar, T Lukasiewicz
arXiv preprint arXiv:2304.03674, 2023
52023
Closing the loop in medical decision support by understanding clinical decision-making: A case study on organ transplantation
Y Qin*, F Imrie*, A Hüyük, D Jarrett, A Gimson, M van der Schaar
Advances in Neural Information Processing Systems 34, 2021
52021
Assessing eligibility for lung cancer screening using parsimonious ensemble machine learning models: A development and validation study
T Callender, F Imrie, B Cebere, N Pashayan, N Navani, M van der Schaar, ...
PLOS Medicine 20 (10), e1004287, 2023
4*2023
Improving Adaptive Conformal Prediction Using Self-Supervised Learning
N Seedat*, A Jeffares*, F Imrie, M van der Schaar
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
42023
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