| NVAE: A deep hierarchical variational autoencoder A Vahdat, J Kautz Neural Information Processing Systems (NeurIPS), 2020 | 930 | 2020 |
| ediff-i: Text-to-image diffusion models with an ensemble of expert denoisers Y Balaji, S Nah, X Huang, A Vahdat, J Song, Q Zhang, K Kreis, M Aittala, ... arXiv preprint arXiv:2211.01324, 2022 | 589 | 2022 |
| 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 | 587 | 2016 |
| Score-based Generative Modeling in Latent Space A Vahdat, K Kreis, J Kautz Neural Information Processing Systems (NeurIPS), 2021 | 559 | 2021 |
| Tackling the Generative Learning Trilemma with Denoising Diffusion GANs Z Xiao, K Kreis, A Vahdat International Conference on Learning Representations (ICLR), 2022 | 471 | 2022 |
| 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 | 471 | 2021 |
| Diffusion Models for Adversarial Purification W Nie, B Guo, Y Huang, C Xiao, A Vahdat, A Anandkumar International Conference on Machine Learning (ICML), 2022 | 372 | 2022 |
| Lion: Latent point diffusion models for 3d shape generation A Vahdat, F Williams, Z Gojcic, O Litany, S Fidler, K Kreis Advances in Neural Information Processing Systems (NeurIPS), 2022 | 370 | 2022 |
| Toward robustness against label noise in training deep discriminative neural networks A Vahdat Neural Information Processing Systems (NeurIPS), 2017 | 357 | 2017 |
| Open-vocabulary panoptic segmentation with text-to-image diffusion models J Xu, S Liu, A Vahdat, W Byeon, X Wang, S De Mello IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2955-2966, 2023 | 320 | 2023 |
| 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 | 295 | 2016 |
| A robust learning approach to domain adaptive object detection M Khodabandeh, A Vahdat, M Ranjbar, WG Macready International Conference on Computer Vision (ICCV), 2019 | 289 | 2019 |
| A-vit: Adaptive tokens for efficient vision transformer H Yin, A Vahdat, JM Alvarez, A Mallya, J Kautz, P Molchanov IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 10809 …, 2022 | 258* | 2022 |
| Score-Based Generative Modeling with Critically-Damped Langevin Diffusion T Dockhorn, A Vahdat, K Kreis International Conference on Learning Representations (ICLR), 2022 | 219 | 2022 |
| Pseudoinverse-guided diffusion models for inverse problems J Song, A Vahdat, M Mardani, J Kautz International Conference on Learning Representations (ICLR), 2022 | 167 | 2022 |
| Physdiff: Physics-guided human motion diffusion model Y Yuan, J Song, U Iqbal, A Vahdat, J Kautz IEEE/CVF International Conference on Computer Vision (CVPR), 16010-16021, 2023 | 166 | 2023 |
| 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 | 141 | 2020 |
| 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 | 122 | 2019 |
| 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 | 117 | 2020 |
| I SB: Image-to-Image Schr\" odinger Bridge GH Liu, A Vahdat, DA Huang, EA Theodorou, W Nie, A Anandkumar International Conference on Machine Learning (ICML), 2023 | 110 | 2023 |
Jan KautzVice President of Research, NVIDIA ResearchVerified email at nvidia.com
