| Key-value memory networks for directly reading documents A Miller, A Fisch, J Dodge, AH Karimi, A Bordes, J Weston EMNLP: Empirical Methods in Natural Language Processing, 2016 | 557 | 2016 |
| MACE: Model-Agnostic Counterfactual Explanations for Consequential Decisions AH Karimi, G Barthe, B Belle, I Valera AISTATS 2020, 2019 | 62* | 2019 |
| Algorithmic Recourse: from Counterfactual Explanations to Interventions AH Karimi, B Schölkopf, I Valera ACM FAccT 2021, 2020 | 39 | 2020 |
| Algorithmic recourse under imperfect causal knowledge: a probabilistic approach AH Karimi, J von Kügelgen, B Schölkopf, I Valera NeurIPS 2020, 2020 | 28 | 2020 |
| A survey of algorithmic recourse: definitions, formulations, solutions, and prospects AH Karimi, G Barthe, B Schölkopf, I Valera arXiv preprint arXiv:2010.04050, 2020 | 27 | 2020 |
| Automated detection and cell density assessment of keratocytes in the human corneal stroma from ultrahigh resolution optical coherence tomograms AH Karimi, A Wong, K Bizheva Biomedical Optics Express, 2011 | 23 | 2011 |
| JADE: Joint autoencoders for dis-entanglement E Banijamali, AH Karimi, A Wong, A Ghodsi NeurIPS 2017 Workshop on Learning Disentangled Representations, 2017 | 11* | 2017 |
| Discovery Radiomics via a Mixture of Deep ConvNet Sequencers for Multi-parametric MRI Prostate Cancer Classification AH Karimi, MJ Shafiee, F Khalvati, MA Haider, A Ghodsi, A Wong ICIAR: International Conference on Image Analysis and Recognition, 2017 | 7 | 2017 |
| On the fairness of causal algorithmic recourse J von Kügelgen, AH Karimi, U Bhatt, I Valera, A Weller, B Schölkopf arXiv preprint arXiv:2010.06529, 2020 | 6 | 2020 |
| Distance correlation autoencoder R Wang, AH Karimi, A Ghodsi IJCNN: IEEE International Joint Conference on Neural Networks, 2018 | 6* | 2018 |
| Spatio-temporal saliency detection using abstracted fully-connected graphical models AH Karimi, MJ Shafiee, C Scharfenberger, I BenDaya, S Haider, ... ICIP: IEEE International Conference on Image Processing, 2016 | 6 | 2016 |
| Deep Variational Sufficient Dimensionality Reduction E Banijamali, AH Karimi, A Ghodsi NeurIPS 2019 Workshop on Bayesian Deep Learning, 2018 | 3 | 2018 |
| SRP: Efficient class-aware embedding learning for large-scale data via supervised random projections AH Karimi, A Wong, A Ghodsi arXiv preprint arXiv:1811.03166, 2018 | 3 | 2018 |
| Key-Value Memory Networks AH Miller, AJ Fisch, JD Dodge, AH Karimi, A Bordes, JE Weston US Patent App. 16/002,463, 2018 | 2 | 2018 |
| A Summary Of The Kernel Matrix, And How To Learn It Effectively Using Semidefinite Programming AH Karimi arXiv preprint arXiv:1709.06557, 2017 | 2 | 2017 |
| Key-Value memory networks for directly reading documents (EMNLP16) AH Miller, A Fisch, J Dodge, AH Karimi, A Bordes, J Weston | 2 | 2016 |
| Scaling Guarantees for Nearest Counterfactual Explanations K Mohammadi, AH Karimi, G Barthe, I Valera ACM AIES 2021, 2020 | 1 | 2020 |
| Exploring new forms of random projections for prediction and dimensionality reduction in big-data regimes AH Karimi University of Waterloo, 2018 | 1 | 2018 |
| Ensembles of Random Projections for Nonlinear Dimensionality Reduction AH Karimi, MJ Shafiee, A Ghodsi, A Wong JCVIS: Journal of Computational Vision and Imaging Systems, 2017 | 1 | 2017 |
| Synthesizing deep neural network architectures using biological synaptic strength distributions AH Karimi, MJ Shafiee, A Ghodsi, A Wong arXiv preprint arXiv:1707.00081, 2017 | 1 | 2017 |
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