Tameem Adel

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Taco CohenQualcomm AI ResearchVerified email at qti.qualcomm.com
Max WellingCAIO CuspAI & Professor Machine Learning, University of AmsterdamVerified email at uva.nl
Adrian WellerDirector of Research, Machine Learning, University of CambridgeVerified email at eng.cam.ac.uk
Luisa ZintgrafDeepMindVerified email at deepmind.com
Han ZhaoDepartment of Computer Science, University of Illinois Urbana-ChampaignVerified email at illinois.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Alexander WongCanada Research Chair FIET FInstP FRSPH FRGS FGS FRSA FISDDE, Systems Design, University of WaterlooVerified email at uwaterloo.ca
Geoff GordonProfessor of Machine Learning, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Richard E TurnerProfessor, University of CambridgeVerified email at cam.ac.uk
Daniel W StashukProfessor, Systems Design Engineering, University of WaterlooVerified email at uwaterloo.ca
Isabel ValeraSaarland University and Max Planck Institute for Software SystemsVerified email at cs.uni-saarland.de
José Miguel Hernández-LobatoProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
Javier AntoranUniversity of CambridgeVerified email at cam.ac.uk
David BalduzziXTX MarketsVerified email at google.com
Ali GhodsiProfessor of Statistics and Computer Science, University of WaterlooVerified email at uwaterloo.ca
Edward MeedsMicrosoft Research CambridgeVerified email at microsoft.com
Daniel LizotteAssociate Professor of Computer Science; Associate Professor of Epidemiology and BiostatisticsVerified email at uwo.ca
Ruth UrnerAssociate Professor, York University, TorontoVerified email at eecs.yorku.ca
Francesco MasulliFull Professor of Computer Science, University of Genoa (ITALY)Verified email at unige.it
Stefano RovettaAssociate professor of Computer Science, DIBRIS, University of Genova, ItalyVerified email at unige.it

Tameem Adel

Machine Learning Group, University of Cambridge

Verified email at uwaterloo.ca - Homepage

Machine Learning Probabilistic Graphical Models Bayesian Inference Deep Learning MRI


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Visualizing deep neural network decisions: Prediction difference analysis LM Zintgraf, TS Cohen, T Adel, M Welling arXiv preprint arXiv:1702.04595, 2017	882	2017
One-network adversarial fairness T Adel, I Valera, Z Ghahramani, A Weller Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 2412-2420, 2019	146	2019
Getting a clue: A method for explaining uncertainty estimates J Antorán, U Bhatt, T Adel, A Weller, JM Hernández-Lobato arXiv preprint arXiv:2006.06848, 2020	135	2020
Conditional learning of fair representations H Zhao, A Coston, T Adel, GJ Gordon arXiv preprint arXiv:1910.07162, 2019	125	2019
Discovering interpretable representations for both deep generative and discriminative models T Adel, Z Ghahramani, A Weller International Conference on Machine Learning, 50-59, 2018	110	2018
Continual Learning with Adaptive Weights (CLAW) T Adel, H Zhao, RE Turner International Conference on Learning Representations, 2020	88	2020
Learning the Structure of Sum-Product Networks via an SVD-based Algorithm. T Adel, D Balduzzi, A Ghodsi UAI, 32-41, 2015	82	2015
A new method to visualize deep neural networks LM Zintgraf, TS Cohen, M Welling arXiv preprint arXiv:1603.02518, 2016	63	2016
Collapsed variational inference for sum-product networks H Zhao, T Adel, G Gordon, B Amos International conference on machine learning, 1310-1318, 2016	51	2016
Human Centered Artificial Intelligence: Weaving UX into Algorithmic Decision Making. RR Bond, MD Mulvenna, H Wan, DD Finlay, A Wong, A Koene, R Brisk, ... RoCHI, 2-9, 2019	50	2019
Electrodiagnosis in new frontiers of clinical research H Turker BoD–Books on Demand, 2013	35	2013
Visualizing deep neural network decisions: Prediction difference analysis. arXiv 2017 LM Zintgraf, TS Cohen, T Adel, M Welling arXiv preprint arXiv:1702.04595, 0	34
Uncertainty estimation in bayesian neural networks and links to interpretability LR Chai Master's Thesis, Massachusetts Institute of Technology, 2018	33	2018
Unsupervised domain adaptation with a relaxed covariate shift assumption T Adel, H Zhao, A Wong Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017	32	2017
Learning Bayesian networks with incomplete data by augmentation T Adel, C de Campos Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017	21	2017
3D scattering transforms for disease classification in neuroimaging T Adel, T Cohen, M Caan, M Welling, AGEhIV study group, ... NeuroImage: Clinical 14, 506-517, 2017	15	2017
Automatic variational ABC A Moreno, T Adel, E Meeds, JM Rehg, M Welling arXiv preprint arXiv:1606.08549, 2016	15	2016
A probabilistic covariate shift assumption for domain adaptation T Adel, A Wong Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015	13	2015
Generative multiple-instance learning models for quantitative electromyography T Adel, B Smith, R Urner, D Stashuk, DJ Lizotte arXiv preprint arXiv:1309.6811, 2013	13	2013
Visualizing deep neural network decisions: prediction difference analysis (2017) LM Zintgraf, TS Cohen, T Adel, M Welling arXiv preprint arXiv:1702.04595, 1-12, 0	11

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