| AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias RKE Bellamy, K Dey, M Hind, SC Hoffman, S Houde, K Kannan, P Lohia, ... IBM Journal of Research and Development 63 (4/5), 4: 1-4: 15, 2019 | 1742 | 2019 |
| Variational inference of disentangled latent concepts from unlabeled observations A Kumar, P Sattigeri, A Balakrishnan International Conference on Learning Representations (ICLR), 2018 | 596 | 2018 |
| One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ... arXiv preprint arXiv:1909.03012, 2019 | 576* | 2019 |
| Uncertainty as a form of transparency: Measuring, communicating, and using uncertainty U Bhatt, J Antorán, Y Zhang, QV Liao, P Sattigeri, R Fogliato, G Melançon, ... Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 401-413, 2021 | 293 | 2021 |
| Fairness GAN: Generating datasets with fairness properties using a generative adversarial network P Sattigeri, SC Hoffman, V Chenthamarakshan, KR Varshney IBM Journal of Research and Development 63 (4/5), 3: 1-3: 9, 2019 | 260* | 2019 |
| Semi-supervised learning with gans: Manifold invariance with improved inference A Kumar, P Sattigeri, T Fletcher Advances in neural information processing systems 30, 2017 | 237* | 2017 |
| Co-regularized alignment for unsupervised domain adaptation A Kumar, P Sattigeri, K Wadhawan, L Karlinsky, R Feris, B Freeman, ... Advances in neural information processing systems 31, 2018 | 203 | 2018 |
| Ar-net: Adaptive frame resolution for efficient action recognition Y Meng, CC Lin, R Panda, P Sattigeri, L Karlinsky, A Oliva, K Saenko, ... Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 179 | 2020 |
| Ai explainability 360 toolkit V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ... Proceedings of the 3rd ACM India Joint International Conference on Data …, 2021 | 117 | 2021 |
| Fairness of classifiers across skin tones in dermatology NM Kinyanjui, T Odonga, C Cintas, NCF Codella, R Panda, P Sattigeri, ... International Conference on Medical Image Computing and Computer-Assisted …, 2020 | 100 | 2020 |
| Tafssl: Task-adaptive feature sub-space learning for few-shot classification M Lichtenstein, P Sattigeri, R Feris, R Giryes, L Karlinsky European Conference on Computer Vision, 522-539, 2020 | 92 | 2020 |
| OnlineAugment: Online data augmentation with less domain knowledge Z Tang, Y Gao, L Karlinsky, P Sattigeri, R Feris, D Metaxas Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 79 | 2020 |
| Optimizing mode connectivity via neuron alignment N Tatro, PY Chen, P Das, I Melnyk, P Sattigeri, R Lai Advances in Neural Information Processing Systems 33, 15300-15311, 2020 | 78 | 2020 |
| Treeview: Peeking into deep neural networks via feature-space partitioning JJ Thiagarajan, B Kailkhura, P Sattigeri, KN Ramamurthy arXiv preprint arXiv:1611.07429, 2016 | 77 | 2016 |
| Adafuse: Adaptive temporal fusion network for efficient action recognition Y Meng, R Panda, CC Lin, P Sattigeri, L Karlinsky, K Saenko, A Oliva, ... arXiv preprint arXiv:2102.05775, 2021 | 73 | 2021 |
| Optimizing kernel machines using deep learning H Song, JJ Thiagarajan, P Sattigeri, A Spanias IEEE transactions on neural networks and learning systems 29 (11), 5528-5540, 2018 | 69 | 2018 |
| Estimating skin tone and effects on classification performance in dermatology datasets NM Kinyanjui, T Odonga, C Cintas, NCF Codella, R Panda, P Sattigeri, ... arXiv preprint arXiv:1910.13268, 2019 | 65 | 2019 |
| Understanding unequal gender classification accuracy from face images V Muthukumar, T Pedapati, N Ratha, P Sattigeri, CW Wu, B Kingsbury, ... arXiv preprint arXiv:1812.00099, 2018 | 65 | 2018 |
| AI Fairness 360: an extensible toolkit for detecting RKE Bellamy, K Dey, M Hind, SC Hoffman, S Houde, K Kannan, P Lohia, ... Understanding, and Mitigating Unwanted Algorithmic Bias 2, 2018 | 56 | 2018 |
| Quantitative resolution of nanoparticle sizes using single particle inductively coupled plasma mass spectrometry with the K-means clustering algorithm X Bi, S Lee, JF Ranville, P Sattigeri, A Spanias, P Herckes, P Westerhoff Journal of Analytical Atomic Spectrometry 29 (9), 1630-1639, 2014 | 53 | 2014 |
Kush R. VarshneyIBM ResearchVerified email at us.ibm.com
