| Learning from uncertain concepts via test time interventions I Sheth, AA Rahman, LR Sevyeri, M Havaei, SE Kahou Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022, 0 | 11* | |
| Adabest: Minimizing client drift in federated learning via adaptive bias estimation F Varno, M Saghayi, L Rafiee Sevyeri, S Gupta, S Matwin, M Havaei European Conference on Computer Vision, 710-726, 2022 | 7 | 2022 |
| Unsupervised anomaly detection with a GAN augmented autoencoder L Rafiee, T Fevens Artificial Neural Networks and Machine Learning–ICANN 2020: 29th …, 2020 | 7 | 2020 |
| Ad-cgan: Contrastive generative adversarial network for anomaly detection LR Sevyeri, T Fevens International Conference on Image Analysis and Processing, 322-334, 2022 | 5 | 2022 |
| Surface realization using pretrained language models F Farahnak, L Rafiee, L Kosseim, T Fevens Proceedings of the Third Workshop on Multilingual Surface Realisation, 57-63, 2020 | 5 | 2020 |
| The Concordia NLG Surface Realizer at SRST 2019 F Farahnak, L Rafiee, L Kosseim, T Fevens Proceedings of the 2nd Workshop on Multilingual Surface Realisation (MSR …, 2019 | 3 | 2019 |
| Transparent anomaly detection via concept-based explanations LR Sevyeri, I Sheth, F Farahnak, SA Enger arXiv preprint arXiv:2310.10702, 2023 | 2 | 2023 |
| On the effectiveness of generative adversarial network on anomaly detection LR Sevyeri, T Fevens arXiv preprint arXiv:2112.15541, 2021 | 2 | 2021 |
| Source-free domain adaptation requires penalized diversity LR Sevyeri, I Sheth, F Farahnak, A See, SE Kahou, T Fevens, M Havaei arXiv preprint arXiv:2304.02798, 2023 | 1 | 2023 |
| Tackling Distribution Shift-Detection and Mitigation L Rafiee Sevyeri Concordia University, 2022 | | 2022 |
| Contrastive Generative Adversarial Network for Anomaly Detection LR Sevyeri, T Fevens | | 2021 |
Thomas FevensProfessor, Department of Computer Science and Software Engineering, Concordia University, MontrealVerified email at cse.concordia.ca
