Tameem Adel

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 20

Top Topics

Artificial Intelligence

Variational Inference

Covariate Shift

Learning Bayesian Networks

Top Venues

Publications

Tameem Adel, Sam Bilson, Mark Levene, Andrew Thompson
Trustworthy Artificial Intelligence in the Context of Metrology. CoRR (2024)
Tameem Adel
Similarity-Based Adaptation for Task-Aware and Task-Free Continual Learning. J. Artif. Intell. Res. 80 (2024)
Tameem Adel
Probabilistic Adaptation for Meta-Learning. ESANN (2023)
Tameem Adel, Mark Levene
A General Model for Side Information in Neural Networks. Algorithms 16 (11) (2023)
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández-Lobato
Getting a CLUE: A Method for Explaining Uncertainty Estimates. ICLR (2021)
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández-Lobato
Getting a CLUE: A Method for Explaining Uncertainty Estimates. CoRR (2020)
Tameem Adel, Han Zhao, Richard E. Turner
Continual Learning with Adaptive Weights (CLAW). ICLR (2020)
Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon
Conditional Learning of Fair Representations. ICLR (2020)
Raymond R. Bond, Maurice D. Mulvenna, Hui Wan, Dewar D. Finlay, Alexander Wong, Ansgar Koene, Rob Brisk, Jennifer Boger, Tameem Adel
Human Centered Artificial Intelligence: Weaving UX into Algorithmic Decision Making. RoCHI (2019)
Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon
Conditional Learning of Fair Representations. CoRR (2019)
Tameem Adel, Han Zhao, Richard E. Turner
Continual Learning with Adaptive Weights (CLAW). CoRR (2019)
Tameem Adel, Isabel Valera, Zoubin Ghahramani, Adrian Weller
One-Network Adversarial Fairness. AAAI (2019)
Tameem Adel, Adrian Weller
TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning. ICML (2019)
Tameem Adel, Zoubin Ghahramani, Adrian Weller
Discovering Interpretable Representations for Both Deep Generative and Discriminative Models. ICML (2018)
Luisa M. Zintgraf, Taco S. Cohen, Tameem Adel, Max Welling
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis. ICLR (Poster) (2017)
Luisa M. Zintgraf, Taco S. Cohen, Tameem Adel, Max Welling
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis. CoRR (2017)
Tameem Adel, Han Zhao, Alexander Wong
Unsupervised Domain Adaptation with a Relaxed Covariate Shift Assumption. AAAI (2017)
Tameem Adel, Cassio P. de Campos
Learning Bayesian Networks with Incomplete Data by Augmentation. AAAI (2017)
Tameem Adel, Cassio P. de Campos
Learning Bayesian Networks without Assuming Missing at Random. CoRR (2016)
Han Zhao, Tameem Adel, Geoffrey J. Gordon, Brandon Amos
Collapsed Variational Inference for Sum-Product Networks. ICML (2016)
Tameem Adel, Alexander Wong
A Probabilistic Covariate Shift Assumption for Domain Adaptation. AAAI (2015)
Tameem Adel, David Balduzzi, Ali Ghodsi
Learning the Structure of Sum-Product Networks via an SVD-based Algorithm. UAI (2015)
Tameem Adel, Alexander Wong, Daniel W. Stashuk
A Weakly Supervised Learning Approach based on Spectral Graph-Theoretic Grouping. CoRR (2015)
Tameem Adel, Benn Smith, Ruth Urner, Daniel W. Stashuk, Daniel J. Lizotte
Generative Multiple-Instance Learning Models For Quantitative Electromyography. CoRR (2013)
Tameem Adel, Benn Smith, Ruth Urner, Daniel W. Stashuk, Daniel J. Lizotte
Generative Multiple-Instance Learning Models For Quantitative Electromyography. UAI (2013)
Tameem Adel, Benn Smith, Daniel W. Stashuk
Muscle categorization using PDF estimation and Naive Bayes classification. EMBC (2012)
Hossein Parsaei, Daniel W. Stashuk, Tameem Adel
Decomposition of intramuscular EMG signals using a knowledge -based certainty classifier algorithm. EMBC (2012)
Stefano Rovetta, Francesco Masulli, Tameem Adel
Tuning Graded Possibilistic Clustering by Visual Stability Analysis. WILF (2011)
Tameem Adel, Mohamed Ismail
ASCM: An accelerated soft c-means clustering algorithm. ISDA (2010)