| NVAE: A deep hierarchical variational autoencoder A Vahdat, J Kautz Neural Information Processing Systems (NeurIPS), 2020 | 676 | 2020 |
| A hierarchical deep temporal model for group activity recognition MS Ibrahim, S Muralidharan, Z Deng, A Vahdat, G Mori Computer Vision and Pattern Recognition (CVPR), 2016 | 514 | 2016 |
| Score-based Generative Modeling in Latent Space A Vahdat, K Kreis, J Kautz Neural Information Processing Systems (NeurIPS), 2021 | 339 | 2021 |
| Toward robustness against label noise in training deep discriminative neural networks A Vahdat Neural Information Processing Systems (NeurIPS), 2017 | 327 | 2017 |
| See through Gradients: Image Batch Recovery via GradInversion H Yin, A Mallya, A Vahdat, JM Alvarez, J Kautz, P Molchanov Computer Vision and Pattern Recognition (CVPR), 2021 | 305 | 2021 |
| Structure inference machines: Recurrent neural networks for analyzing relations in group activity recognition Z Deng, A Vahdat, H Hu, G Mori Computer Vision and Pattern Recognition (CVPR), 2016 | 279 | 2016 |
| ediffi: Text-to-image diffusion models with an ensemble of expert denoisers Y Balaji, S Nah, X Huang, A Vahdat, J Song, K Kreis, M Aittala, T Aila, ... arXiv preprint arXiv:2211.01324, 2022 | 265 | 2022 |
| Tackling the Generative Learning Trilemma with Denoising Diffusion GANs Z Xiao, K Kreis, A Vahdat International Conference on Learning Representations (ICLR), 2022 | 254 | 2022 |
| A robust learning approach to domain adaptive object detection M Khodabandeh, A Vahdat, M Ranjbar, WG Macready International Conference on Computer Vision (ICCV), 2019 | 231 | 2019 |
| Diffusion Models for Adversarial Purification W Nie, B Guo, Y Huang, C Xiao, A Vahdat, A Anandkumar International Conference on Machine Learning (ICML), 2022 | 155 | 2022 |
| LION: Latent point diffusion models for 3D shape generation X Zeng, A Vahdat, F Williams, Z Gojcic, O Litany, S Fidler, K Kreis arXiv preprint arXiv:2210.06978, 2022 | 145 | 2022 |
| A-vit: Adaptive tokens for efficient vision transformer H Yin, A Vahdat, JM Alvarez, A Mallya, J Kautz, P Molchanov Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 133* | 2022 |
| Score-Based Generative Modeling with Critically-Damped Langevin Diffusion T Dockhorn, A Vahdat, K Kreis International Conference on Learning Representations (ICLR), 2022 | 128 | 2022 |
| Contrastive learning for weakly supervised phrase grounding T Gupta, A Vahdat, G Chechik, X Yang, J Kautz, D Hoiem European Conference on Computer Vision (ECCV), 2020 | 110 | 2020 |
| A discriminative key pose sequence model for recognizing human interactions A Vahdat, B Gao, M Ranjbar, G Mori International Conference on Computer Vision Workshops (ICCV Workshops), 2011 | 104 | 2011 |
| CATARACTS: Challenge on automatic tool annotation for cataRACT surgery H Al Hajj, M Lamard, PH Conze, S Roychowdhury, X Hu, G Maršalkaitė, ... Medical Image Analysis (MedIA) 52, 24-41, 2019 | 103 | 2019 |
| Visual recognition by counting instances: A multi-instance cardinality potential kernel H Hajimirsadeghi, W Yan, A Vahdat, G Mori Computer Vision and Pattern Recognition (CVPR), 2015 | 99 | 2015 |
| Semi-supervised semantic image segmentation with self-correcting networks MS Ibrahim, A Vahdat, M Ranjbar, WG Macready Computer Vision and Pattern Recognition (CVPR), 2020 | 92 | 2020 |
| VAEBM: A symbiosis between variational autoencoders and energy-based models Z Xiao, K Kreis, J Kautz, A Vahdat International Conference on Learning Representations (ICLR), 2020 | 87 | 2020 |
| A contrastive learning approach for training variational autoencoder priors J Aneja, A Schwing, J Kautz, A Vahdat Advances in Neural Information Processing Systems (NeurIPS) 34, 2021 | 78* | 2021 |
Greg MoriResearch Director, Borealis AI; Professor, School of Computing Science, Simon Fraser UniversityVerified email at cs.sfu.ca
