| Differentially Private Federated Learning: A Client Level Perspective RC Geyer, T Klein, M Nabi Conference on Advances in Neural Information Processing Systems (NIPS 2017 …, 2017 | 1474 | 2017 |
| Abnormal Event Detection in Videos using Generative Adversarial Nets M Ravanbakhsh, M Nabi, E Sangineto, L Marcenaro, C Regazzoni, ... IEEE International Conference on Image Processing (ICIP), 2017 | 560 | 2017 |
| Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning O Ostapenko, M Puscas, T Klein, P Jähnichen, M Nabi CVPR 2019, 2019 | 308 | 2019 |
| Plug-and-play CNN for crowd motion analysis: An application in abnormal event detection M Ravanbakhsh, M Nabi, H Mousavi, E Sangineto, N Sebe WACV 2018, 2018 | 267 | 2018 |
| Training Adversarial Discriminators for Cross-channel Abnormal Event Detection in Crowds M Ravanbakhsh, E Sangineto, M Nabi, N Sebe WACV 2019, 2019 | 252 | 2019 |
| A Unified Objective for Novel Class Discovery E Fini, E Sangineto, S Lathuilière, Z Zhong, M Nabi, E Ricci ICCV 2021, 2021 | 152 | 2021 |
| A unified objective for novel class discovery E Fini, E Sangineto, S Lathuilière, Z Zhong, M Nabi, E Ricci Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 152 | 2021 |
| Self Paced Deep Learning for Weakly Supervised Object Detection E Sangineto*, M Nabi*, D Culibrk, N Sebe IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2018 | 131 | 2018 |
| FOIL it! Find One mismatch between Image and Language caption R Shekhar, S Pezzelle, Y Klimovich, A Herbelot, M Nabi, E Sangineto, ... ACL 2017, 2017 | 130 | 2017 |
| Multimodal Self-supervised Learning for Medical Image Analysis A Taleb, C Lippert, T Klein, M Nabi International Conference on Information Processing in Medical Imaging, 661-673, 2021 | 128 | 2021 |
| solo-learn: A Library of Self-supervised Methods for Visual Representation Learning. VGT Da Costa, E Fini, M Nabi, N Sebe, E Ricci Journal of Machine Learning Research (JMLR), 2022 | 111 | 2022 |
| Multimodal Prototypical Networks for Few-shot Learning F Pahde, M Puscas, T Klein, M Nabi WACV 2021, 2021 | 87 | 2021 |
| Learning to Answer by Learning to Ask: Getting the Best of GPT-2 and BERT Worlds T Klein, M Nabi arXiv preprint arXiv:1911.02365, 2019 | 82 | 2019 |
| Novel dataset for fine-grained abnormal behavior understanding in crowd H Rabiee, J Haddadnia, H Mousavi, M Kalantarzadeh, M Nabi, V Murino 2016 13th IEEE International Conference on Advanced Video and Signal Based …, 2016 | 76 | 2016 |
| Online Continual Learning under Extreme Memory Constraints E Fini, S Lathuilière, E Sangineto, M Nabi, E Ricci ECCV 2020, 2020 | 72 | 2020 |
| Contrastive Self-Supervised Learning for Commonsense Reasoning T Klein, M Nabi ACL 2020, 2020 | 63 | 2020 |
| Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation G Yang, E Fini, D Xu, P Rota, M Ding, M Nabi, X Alameda-Pineda, E Ricci IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2022 | 55 | 2022 |
| Crowd motion monitoring using tracklet-based commotion measure H Mousavi, M Nabi, H Kiani, A Perina, V Murino 2015 IEEE International Conference on Image Processing (ICIP), 2354-2358, 2015 | 52 | 2015 |
| Detection and localization of crowd behavior using a novel tracklet-based model H Rabiee, H Mousavi, M Nabi, M Ravanbakhsh International Journal of Machine Learning and Cybernetics 9, 1999-2010, 2018 | 49 | 2018 |
| Abnormality detection with improved histogram of oriented tracklets H Mousavi, M Nabi, HK Galoogahi, A Perina, V Murino International Conference on Image Analysis and Processing, 722-732, 2015 | 47 | 2015 |
Tassilo KleinPrincipal Scientist @ SAP AI Research在 sap.com 的电子邮件经过验证
