| 2023 | ESANN | Probabilistic Adaptation for Meta-Learning. | Tameem Adel |
| 2021 | ICLR | Getting a CLUE: A Method for Explaining Uncertainty Estimates. | Javier Antorn, Umang Bhatt, Tameem Adel, Adrian Weller, Jos Miguel Hernndez-Lobato |
| 2020 | ICLR | Conditional Learning of Fair Representations. | Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon |
| 2020 | ICLR | Continual Learning with Adaptive Weights (CLAW). | Tameem Adel, Han Zhao, Richard E. Turner |
| 2019 | AAAI | One-Network Adversarial Fairness. | Tameem Adel, Isabel Valera, Zoubin Ghahramani, Adrian Weller |
| 2019 | ICML | TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning. | Tameem Adel, Adrian Weller |
| 2018 | ICML | Discovering Interpretable Representations for Both Deep Generative and Discriminative Models. | Tameem Adel, Zoubin Ghahramani, Adrian Weller |
| 2017 | AAAI | Learning Bayesian Networks with Incomplete Data by Augmentation. | Tameem Adel, Cassio P. de Campos |
| 2017 | AAAI | Unsupervised Domain Adaptation with a Relaxed Covariate Shift Assumption. | Tameem Adel, Han Zhao, Alexander Wong |
| 2017 | ICLR | Visualizing Deep Neural Network Decisions: Prediction Difference Analysis. | Luisa M. Zintgraf, Taco S. Cohen, Tameem Adel, Max Welling |
| 2016 | ICML | Collapsed Variational Inference for Sum-Product Networks. | Han Zhao, Tameem Adel, Geoffrey J. Gordon, Brandon Amos |
| 2015 | AAAI | A Probabilistic Covariate Shift Assumption for Domain Adaptation. | Tameem Adel, Alexander Wong |
| 2015 | UAI | Learning the Structure of Sum-Product Networks via an SVD-based Algorithm. | Tameem Adel, David Balduzzi, Ali Ghodsi |
| 2013 | UAI | Generative Multiple-Instance Learning Models For Quantitative Electromyography. | Tameem Adel, Benn Smith, Ruth Urner, Daniel W. Stashuk, Daniel J. Lizotte |
| 2010 | ISDA | ASCM: An accelerated soft c-means clustering algorithm. | Tameem Adel, Mohamed Ismail |