Ehsan Abbasnejad
Ehsan Abbasnejad
Australian Institute for Machine Learning, University of Adelaide
Verified email at - Homepage
Cited by
Cited by
Infinite Variational Autoencoder for Semi-Supervised Learning
E Abbasnejad, A Dick, A van den Hengel
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu …, 2017
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
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
Low-rank linear cold-start recommendation from social data
S Sedhain, A Menon, S Sanner, L Xie, D Braziunas
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
Learning what makes a difference from counterfactual examples and gradient supervision
D Teney, E Abbasnedjad, A Hengel
European Conference on Computer Vision, 580-599, 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
A survey of the state of the art in learning the kernels
ME Abbasnejad, D Ramachandram, R Mandava
Knowledge and information systems 31 (2), 193-221, 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
Symbolic variable elimination for discrete and continuous graphical models
S Sanner, E Abbasnejad
Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012
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
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
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
Symbolic dynamic programming for continuous state and action mdps
Z Zamani, S Sanner, C Fang
Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 1839-1845, 2012
Reinforcement learning with attention that works: A self-supervised approach
A Manchin, E Abbasnejad, A Hengel
International conference on neural information processing, 223-230, 2019
Adaptive neuro-surrogate-based optimisation method for wave energy converters placement optimisation
M Neshat, E Abbasnejad, Q Shi, B Alexander, M Wagner
International Conference on Neural Information Processing, 353-366, 2019
Joint probabilistic matching using m-best solutions
S Hamid Rezatofighi, A Milan, Z Zhang, Q Shi, A Dick, I Reid
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
Unshuffling data for improved generalization
D Teney, E Abbasnejad, A Hengel
arXiv preprint arXiv:2002.11894, 2020
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
Deep auto-set: A deep auto-encoder-set network for activity recognition using wearables
AA Varamin, E Abbasnejad, Q Shi, DC Ranasinghe, H Rezatofighi
Proceedings of the 15th EAI International Conference on Mobile and …, 2018
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