| Februus: Input purification defense against trojan attacks on deep neural network systems BG Doan, E Abbasnejad, DC Ranasinghe Annual computer security applications conference, 897-912, 2020 | 196 | 2020 |
| On the value of out-of-distribution testing: An example of goodhart's law D Teney, E Abbasnejad, K Kafle, R Shrestha, C Kanan, ... Advances in neural information processing systems 33, 407-417, 2020 | 124 | 2020 |
| A deep learning-based evolutionary model for short-term wind speed forecasting: A case study of the Lillgrund offshore wind farm M Neshat, MM Nezhad, E Abbasnejad, S Mirjalili, LB Tjernberg, ... Energy conversion and management 236, 114002, 2021 | 121 | 2021 |
| Learning what makes a difference from counterfactual examples and gradient supervision D Teney, E Abbasnedjad, A van den Hengel Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 108 | 2020 |
| Counterfactual vision and language learning E Abbasnejad, D Teney, A Parvaneh, J Shi, A Hengel Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 102 | 2020 |
| New objective functions for social collaborative filtering J Noel, S Sanner, KN Tran, P Christen, L Xie, EV Bonilla, E Abbasnejad, ... Proceedings of the 21st international conference on World Wide Web, 859-868, 2012 | 95 | 2012 |
| Infinite variational autoencoder for semi-supervised learning M Ehsan Abbasnejad, A Dick, A van den Hengel Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 86 | 2017 |
| Unshuffling data for improved generalization in visual question answering D Teney, E Abbasnejad, A van den Hengel Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 81 | 2021 |
| Using synthetic data to improve facial expression analysis with 3d convolutional networks I Abbasnejad, S Sridharan, D Nguyen, S Denman, C Fookes, S Lucey Proceedings of the IEEE International Conference on Computer Vision …, 2017 | 77 | 2017 |
| Wind turbine power output prediction using a new hybrid neuro-evolutionary method M Neshat, MM Nezhad, E Abbasnejad, S Mirjalili, D Groppi, A Heydari, ... Energy 229, 120617, 2021 | 68 | 2021 |
| Reflection, refraction, and hamiltonian monte carlo H Mohasel Afshar, J Domke Advances in neural information processing systems 28, 2015 | 68 | 2015 |
| A survey of the state of the art in learning the kernels ME Abbasnejad, D Ramachandram, R Mandava Knowledge and information systems 31, 193-221, 2012 | 64 | 2012 |
| Beyond question-based biases: Assessing multimodal shortcut learning in visual question answering C Dancette, R Cadene, D Teney, M Cord Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 59 | 2021 |
| Symbolic variable elimination for discrete and continuous graphical models S Sanner, E Abbasnejad Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 1954-1960, 2012 | 56 | 2012 |
| Evading the simplicity bias: Training a diverse set of models discovers solutions with superior ood generalization D Teney, E Abbasnejad, S Lucey, A Van den Hengel Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 55 | 2022 |
| Reinforcement learning with attention that works: A self-supervised approach A Manchin, E Abbasnejad, A Van Den Hengel Neural Information Processing: 26th International Conference, ICONIP 2019 …, 2019 | 52 | 2019 |
| Distribution based workload modelling of continuous queries in clouds A Khoshkbarforoushha, R Ranjan, R Gaire, E Abbasnejad, L Wang, ... IEEE transactions on Emerging Topics in Computing 5 (1), 120-133, 2016 | 52 | 2016 |
| Deepsetnet: Predicting sets with deep neural networks SH Rezatofighi, VK BG, A Milan, E Abbasnejad, A Dick, I Reid 2017 IEEE International Conference on Computer Vision (ICCV), 5257-5266, 2017 | 50* | 2017 |
| All labels are not created equal: Enhancing semi-supervision via label grouping and co-training I Nassar, S Herath, E Abbasnejad, W Buntine, G Haffari Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 48 | 2021 |
| idarts: Differentiable architecture search with stochastic implicit gradients M Zhang, SW Su, S Pan, X Chang, EM Abbasnejad, R Haffari International Conference on Machine Learning, 12557-12566, 2021 | 46 | 2021 |
Anton van den HengelDirector of Applied Science at Amazon and Director of the Centre for Augmented Reasoning at AIML.Verified email at adelaide.edu.au
