Ehsan Abbasnejad
Ehsan Abbasnejad
Australian Institute for Machine Learning, University of Adelaide
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
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
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
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
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
Reflection, refraction, and hamiltonian monte carlo
H Mohasel Afshar, J Domke
Advances in neural information processing systems 28, 2015
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
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
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
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
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
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
Learning community-based preferences via dirichlet process mixtures of gaussian processes
E Abbasnejad, S Sanner, EV Bonilla, P Poupart
Twenty-third international joint conference on artificial intelligence, 2013
Label filters for large scale multilabel classification
A Niculescu-Mizil, E Abbasnejad
Artificial intelligence and statistics, 1448-1457, 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
Renyi entropy properties of order statistics
M Abbasnejad, NR Arghami
Communications in Statistics—Theory and Methods 40 (1), 40-52, 2010
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
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