ASCM: An accelerated soft c-means clustering algorithm. - Tameem Adel; Mohamed Ismail (ISDA, 2010)

Tuning Graded Possibilistic Clustering by Visual Stability Analysis. - Stefano Rovetta; Francesco Masulli; Tameem Adel (WILF, 2011)

Muscle categorization using PDF estimation and Naive Bayes classification. - Tameem Adel; Benn Smith; Daniel W. Stashuk (EMBC, 2012)

Decomposition of intramuscular EMG signals using a knowledge -based certainty classifier algorithm. - Hossein Parsaei; Daniel W. Stashuk; Tameem Adel (EMBC, 2012)

Generative Multiple-Instance Learning Models For Quantitative Electromyography. - Tameem Adel; Benn Smith; Ruth Urner; Daniel W. Stashuk; Daniel J. Lizotte (UAI, 2013)

A Probabilistic Covariate Shift Assumption for Domain Adaptation. - Tameem Adel; Alexander Wong (AAAI, 2015)

Learning the Structure of Sum-Product Networks via an SVD-based Algorithm. - Tameem Adel; David Balduzzi; Ali Ghodsi 001 (UAI, 2015)

A Weakly Supervised Learning Approach based on Spectral Graph-Theoretic Grouping. - Tameem Adel; Alexander Wong; Daniel W. Stashuk (CoRR, 2015)

Collapsed Variational Inference for Sum-Product Networks. - Han Zhao 002; Tameem Adel; Geoffrey J. Gordon; Brandon Amos (ICML, 2016)

Learning Bayesian Networks without Assuming Missing at Random. - Tameem Adel; Cassio P. de Campos (CoRR, 2016)

Learning Bayesian Networks with Incomplete Data by Augmentation. - Tameem Adel; Cassio P. de Campos (AAAI, 2017)

Unsupervised Domain Adaptation with a Relaxed Covariate Shift Assumption. - Tameem Adel; Han Zhao 002; Alexander Wong (AAAI, 2017)

Visualizing Deep Neural Network Decisions: Prediction Difference Analysis. - Luisa M. Zintgraf; Taco S. Cohen; Tameem Adel; Max Welling (ICLR (Poster), 2017)

Discovering Interpretable Representations for Both Deep Generative and Discriminative Models. - Tameem Adel; Zoubin Ghahramani; Adrian Weller (ICML, 2018)

One-Network Adversarial Fairness. - Tameem Adel; Isabel Valera; Zoubin Ghahramani; Adrian Weller (AAAI, 2019)

TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning. - Tameem Adel; Adrian Weller (ICML, 2019)

Human Centered Artificial Intelligence: Weaving UX into Algorithmic Decision Making. - Raymond R. Bond; Maurice D. Mulvenna; Hui Wan; Dewar D. Finlay; Alexander Wong; Ansgar Koene; Rob Brisk; Jennifer Boger; Tameem Adel (RoCHI, 2019)

Conditional Learning of Fair Representations. - Han Zhao 002; Amanda Coston; Tameem Adel; Geoffrey J. Gordon (ICLR, 2020)

Continual Learning with Adaptive Weights (CLAW). - Tameem Adel; Han Zhao 002; Richard E. Turner (ICLR, 2020)

Getting a CLUE: A Method for Explaining Uncertainty Estimates. - Javier Antorán; Umang Bhatt; Tameem Adel; Adrian Weller; José Miguel Hernández-Lobato (ICLR, 2021)

Probabilistic Adaptation for Meta-Learning. - Tameem Adel (ESANN, 2023)

A General Model for Side Information in Neural Networks. - Tameem Adel; Mark Levene (Algorithms, 2023)

Explaining Time Series Predictions via Relevant Shapelets. - Tameem Adel (ICAAI, 2024)

Automated Class-Imbalanced Learning by Bayesian Optimisation. - Tameem Adel (ICAAI, 2024)

Adversarial Learning of Summary Statistics for Approximate Bayesian Computation. - Tameem Adel (ICAAI, 2024)

Trustworthy Artificial Intelligence in the Context of Metrology. - Tameem Adel; Sam Bilson; Mark Levene; Andrew Thompson 014 (CoRR, 2024)

Similarity-Based Adaptation for Task-Aware and Task-Free Continual Learning. - Tameem Adel (J. Artif. Intell. Res., 2024)

Adaptive Few-Shot Class-Incremental Learning via Latent Variable Models. - Tameem Adel (J. Artif. Intell. Res., 2025)

The Bayesian Approach to Continual Learning: An Overview. - Tameem Adel (CoRR, 2025)