An unsupervised approach to learn the kernel functions: from global influence to local similarity. - M. Ehsan Abbasnejad; Dhanesh Ramachandram; Mandava Rajeswari (Neural Comput. Appl., 2011)

Symbolic Variable Elimination for Discrete and Continuous Graphical Models. - Scott Sanner; Ehsan Abbasnejad (AAAI, 2012)

New objective functions for social collaborative filtering. - Joseph Noel; Scott Sanner; Khoi-Nguyen Tran; Peter Christen; Lexing Xie; Edwin V. Bonilla; Ehsan Abbasnejad; Nicolás Della Penna (WWW, 2012)

A survey of the state of the art in learning the kernels. - M. Ehsan Abbasnejad; Dhanesh Ramachandram; Mandava Rajeswari (Knowl. Inf. Syst., 2012)

Decision-Theoretic Approximations for Machine Learning. - Ehsan Abbasnejad (IJCAI, 2013)

Learning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes. - Ehsan Abbasnejad; Scott Sanner; Edwin V. Bonilla; Pascal Poupart (IJCAI, 2013)

Decision-Theoretic Sparsification for Gaussian Process Preference Learning. - M. Ehsan Abbasnejad; Edwin V. Bonilla; Scott Sanner (ECML/PKDD (2), 2013)

Soccer event detection via collaborative multimodal feature analysis and candidate ranking. - Alfian Abdul Halin; Mandava Rajeswari; Mohammad Abbasnejad (Int. Arab J. Inf. Technol., 2013)

Loss-Calibrated Monte Carlo Action Selection. - Ehsan Abbasnejad; Justin Domke; Scott Sanner (AAAI, 2015)

Linear-Time Gibbs Sampling in Piecewise Graphical Models. - Hadi Mohasel Afshar; Scott Sanner; Ehsan Abbasnejad (AAAI, 2015)

Resource Usage Estimation of Data Stream Processing Workloads in Datacenter Clouds. - Alireza Khoshkbarforoushha; Rajiv Ranjan 001; Raj Gaire 001; Prem Prakash Jayaraman; John G. Hosking; Ehsan Abbasnejad (CoRR, 2015)

Label Filters for Large Scale Multilabel Classification. - Alexandru Niculescu-Mizil; Ehsan Abbasnejad (AISTATS, 2017)

Infinite Variational Autoencoder for Semi-Supervised Learning. - M. Ehsan Abbasnejad; Anthony R. Dick; Anton van den Hengel (CVPR, 2017)

DeepSetNet: Predicting Sets with Deep Neural Networks. - Seyed Hamid Rezatofighi; Vijay Kumar B. G; Anton Milan; Ehsan Abbasnejad; Anthony R. Dick; Ian D. Reid 001 (ICCV, 2017)

Bayesian Conditional Generative Adverserial Networks. - M. Ehsan Abbasnejad; Qinfeng Shi; Iman Abbasnejad; Anton van den Hengel; Anthony R. Dick (CoRR, 2017)

Distribution Based Workload Modelling of Continuous Queries in Clouds. - Alireza Khoshkbarforoushha; Rajiv Ranjan 001; Raj Gaire 001; Ehsan Abbasnejad; Lizhe Wang 001; Albert Y. Zomaya (IEEE Trans. Emerg. Top. Comput., 2017)

Active Learning from Noisy Tagged Images. - M. Ehsan Abbasnejad; Anthony R. Dick; Qinfeng Shi; Anton van den Hengel (BMVC, 2018)

3D Hand Pose Estimation using Simulation and Partial-Supervision with a Shared Latent Space. - Masoud Abdi; Ehsan Abbasnejad; Chee Peng Lim; Saeid Nahavandi (BMVC, 2018)

Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables. - Alireza Abedin Varamin; Ehsan Abbasnejad; Qinfeng Shi; Damith Chinthana Ranasinghe; Seyed Hamid Rezatofighi (MobiQuitous, 2018)

Discriminative Clustering of High-Dimensional Data Using Generative Modeling. - Masoud Abdi; Chee Peng Lim; Shady M. K. Mohamed; Saeid Nahavandi; Ehsan Abbasnejad; Anton van den Hengel (MWSCAS, 2018)

An Active Information Seeking Model for Goal-oriented Vision-and-Language Tasks. - Ehsan Abbasnejad; Qi Wu 001; Iman Abbasnejad; Javen Shi; Anton van den Hengel (CoRR, 2018)

A Generative Adversarial Density Estimator. - M. Ehsan Abbasnejad; Qinfeng Shi; Anton van den Hengel; Lingqiao Liu (CVPR, 2019)

What's to Know? Uncertainty as a Guide to Asking Goal-Oriented Questions. - Ehsan Abbasnejad; Qi Wu 001; Qinfeng Shi; Anton van den Hengel (CVPR, 2019)

Reinforcement Learning with Attention that Works: A Self-Supervised Approach. - Anthony Manchin; Ehsan Abbasnejad; Anton van den Hengel (ICONIP (5), 2019)

Adaptive Neuro-Surrogate-Based Optimisation Method for Wave Energy Converters Placement Optimisation. - Mehdi Neshat; Ehsan Abbasnejad; Qinfeng Shi; Bradley Alexander; Markus Wagner 007 (ICONIP (2), 2019)

Show, Price and Negotiate: A Hierarchical Attention Recurrent Visual Negotiator. - Amin Parvaneh; Ehsan Abbasnejad; Qi Wu 001; Javen Shi (CoRR, 2019)

Follow the Attention: Combining Partial Pose and Object Motion for Fine-Grained Action Detection. - Mohammad Mahdi Kazemi Moghaddam; Ehsan Abbasnejad; Javen Shi (CoRR, 2019)

Deep Single Image Deraining Via Estimating Transmission and Atmospheric Light in rainy Scenes. - Yinglong Wang 002; Qinfeng Shi; Ehsan Abbasnejad; Chao Ma 004; Xiaoping Ma; Bing Zeng (CoRR, 2019)

DeepCleanse: Input Sanitization Framework Against Trojan Attacks on Deep Neural Network Systems. - Bao Gia Doan; Ehsan Abbasnejad; Damith Chinthana Ranasinghe (CoRR, 2019)

On Incorporating Semantic Prior Knowlegde in Deep Learning Through Embedding-Space Constraints. - Damien Teney; Ehsan Abbasnejad; Anton van den Hengel (CoRR, 2019)

Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems. - Bao Gia Doan; Ehsan Abbasnejad; Damith C. Ranasinghe (ACSAC, 2020)

Gold Seeker: Information Gain From Policy Distributions for Goal-Oriented Vision-and-Langauge Reasoning. - Ehsan Abbasnejad; Iman Abbasnejad; Qi Wu 001; Javen Shi; Anton van den Hengel (CVPR, 2020)

Counterfactual Vision and Language Learning. - Ehsan Abbasnejad; Damien Teney; Amin Parvaneh; Javen Shi; Anton van den Hengel (CVPR, 2020)

Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision. - Damien Teney; Ehsan Abbasnejad; Anton van den Hengel (ECCV (10), 2020)

Counterfactual Vision-and-Language Navigation: Unravelling the Unseen. - Amin Parvaneh; Ehsan Abbasnejad; Damien Teney; Qinfeng Shi; Anton van den Hengel (NeurIPS, 2020)

On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law. - Damien Teney; Ehsan Abbasnejad; Kushal Kafle; Robik Shrestha; Christopher Kanan; Anton van den Hengel (NeurIPS, 2020)

An Evolutionary Deep Learning Method for Short-term Wind Speed Prediction: A Case Study of the Lillgrund Offshore Wind Farm. - Mehdi Neshat; Meysam Majidi Nezhad; Ehsan Abbasnejad; Lina Bertling Tjernberg; Davide Astiaso Garcia; Bradley Alexander; Markus Wagner 007 (CoRR, 2020)

Unshuffling Data for Improved Generalization. - Damien Teney; Ehsan Abbasnejad; Anton van den Hengel (CoRR, 2020)

Utilising Prior Knowledge for Visual Navigation: Distil and Adapt. - Mohammad Mahdi Kazemi Moghaddam; Qi Wu 001; Ehsan Abbasnejad; Javen Shi (CoRR, 2020)

Hybrid Neuro-Evolutionary Method for Predicting Wind Turbine Power Output. - Mehdi Neshat; Meysam Majidi Nezhad; Ehsan Abbasnejad; Daniele Groppi; Azim Heydari; Lina Bertling Tjernberg; Davide Astiaso Garcia; Bradley Alexander; Markus Wagner 007 (CoRR, 2020)

GADE: A Generative Adversarial Approach to Density Estimation and its Applications. - M. Ehsan Abbasnejad; Javen Shi; Anton van den Hengel; Lingqiao Liu (Int. J. Comput. Vis., 2020)

Curriculum Learning Effectively Improves Low Data VQA. - Narjes Askarian; Ehsan Abbasnejad; Ingrid Zukerman; Wray L. Buntine; Gholamreza Haffari (ALTA, 2021)

All Labels Are Not Created Equal: Enhancing Semi-Supervision via Label Grouping and Co-Training. - Islam Nassar; Samitha Herath; Ehsan Abbasnejad; Wray L. Buntine; Gholamreza Haffari (CVPR, 2021)

Cross-Modal Visual Question Answering for Remote Sensing Data: The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2021). - Rafael Felix; Boris Repasky; Samuel Hodge; Reza Zolfaghari; Ehsan Abbasnejad; Jamie Sherrah (DICTA, 2021)

Unshuffling Data for Improved Generalization in Visual Question Answering. - Damien Teney; Ehsan Abbasnejad; Anton van den Hengel (ICCV, 2021)

iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients. - Miao Zhang; Steven W. Su; Shirui Pan; Xiaojun Chang; M. Ehsan Abbasnejad; Reza Haffari (ICML, 2021)

Optimistic Agent: Accurate Graph-Based Value Estimation for More Successful Visual Navigation. - Mohammad Mahdi Kazemi Moghaddam; Qi Wu 001; Ehsan Abbasnejad; Javen Shi (WACV, 2021)

Learning for Visual Navigation by Imagining the Success. - Mohammad Mahdi Kazemi Moghaddam; Ehsan Abbasnejad; Qi Wu 001; Javen Shi; Anton van den Hengel (CoRR, 2021)

RamBoAttack: A Robust Query Efficient Deep Neural Network Decision Exploit. - Viet Quoc Vo; Ehsan Abbasnejad; Damith C. Ranasinghe (CoRR, 2021)

A data-driven reservoir simulation for natural gas reservoirs. - Shahdad Ghassemzadeh; Maria Gonzalez Perdomo; Manouchehr Haghighi; Ehsan Abbasnejad (Neural Comput. Appl., 2021)

Active Learning by Feature Mixing. - Amin Parvaneh; Ehsan Abbasnejad; Damien Teney; Reza Haffari; Anton van den Hengel; Javen Qinfeng Shi (CVPR, 2022)

Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization. - Damien Teney; Ehsan Abbasnejad; Simon Lucey; Anton van den Hengel (CVPR, 2022)

Predicting Is Not Understanding: Recognizing and Addressing Underspecification in Machine Learning. - Damien Teney; Maxime Peyrard; Ehsan Abbasnejad (ECCV (23), 2022)

Query Efficient Decision Based Sparse Attacks Against Black-Box Deep Learning Models. - Viet Quoc Vo; Ehsan Abbasnejad; Damith Ranasinghe (ICLR, 2022)

Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial Defense. - Bao Gia Doan; Ehsan Abbasnejad; Javen Qinfeng Shi; Damith C. Ranasinghe (ICML, 2022)

Progressive Class Semantic Matching for Semi-supervised Text Classification. - Hai-Ming Xu; Lingqiao Liu; Ehsan Abbasnejad (NAACL-HLT, 2022)

RamBoAttack: A Robust and Query Efficient Deep Neural Network Decision Exploit. - Viet Quoc Vo; Ehsan Abbasnejad; Damith C. Ranasinghe (NDSS, 2022)

Truncated Matrix Power Iteration for Differentiable DAG Learning. - Zhen Zhang 008; Ignavier Ng; Dong Gong; Yuhang Liu 002; Ehsan Abbasnejad; Mingming Gong; Kun Zhang 001; Javen Qinfeng Shi (NeurIPS, 2022)

Inductive Biases for Low Data VQA: A Data Augmentation Approach. - Narjes Askarian; Ehsan Abbasnejad; Ingrid Zukerman; Wray L. Buntine; Gholamreza Haffari (WACV (Workshops), 2022)

ForeSI: Success-Aware Visual Navigation Agent. - Mohammad Mahdi Kazemi Moghaddam; Ehsan Abbasnejad; Qi Wu 001; Qinfeng (Javen) Shi; Anton van den Hengel (WACV, 2022)

Astock: A New Dataset and Automated Stock Trading based on Stock-specific News Analyzing Model. - Jinan Zou; Haiyao Cao; Lingqiao Liu; Yuhao Lin; Ehsan Abbasnejad; Javen Qinfeng Shi (CoRR, 2022)

EBMs vs. CL: Exploring Self-Supervised Visual Pretraining for Visual Question Answering. - Violetta Shevchenko; Ehsan Abbasnejad; Anthony R. Dick; Anton van den Hengel; Damien Teney (CoRR, 2022)

LAVA: Label-efficient Visual Learning and Adaptation. - Islam Nassar; Munawar Hayat; Ehsan Abbasnejad; Hamid Rezatofighi; Mehrtash Harandi; Gholamreza Haffari (CoRR, 2022)

TnT Attacks! Universal Naturalistic Adversarial Patches Against Deep Neural Network Systems. - Bao Gia Doan; Minhui Xue 001; Shiqing Ma; Ehsan Abbasnejad; Damith C. Ranasinghe (IEEE Trans. Inf. Forensics Secur., 2022)

Show, Price and Negotiate: A Negotiator With Online Value Look-Ahead. - Amin Parvaneh; Ehsan Abbasnejad; Qi Wu 001; Qinfeng (Javen) Shi; Anton van den Hengel (IEEE Trans. Multim., 2022)

Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness. - Bao Gia Doan; Shuiqiao Yang; Paul Montague; Olivier Y. de Vel; Tamas Abraham; Seyit Camtepe; Salil S. Kanhere; Ehsan Abbasnejad; Damith C. Ranasinghe (AAAI, 2023)

SCONE-GAN: Semantic Contrastive learning-based Generative Adversarial Network for an end-to-end image translation. - Iman Abbasnejad; Fabio Zambetta; Flora D. Salim; Timothy Wiley; Jeffrey Chan; Russell Gallagher; Ehsan Abbasnejad (CVPR Workshops, 2023)

Protocon: Pseudo-Label Refinement via Online Clustering and Prototypical Consistency for Efficient Semi-Supervised Learning. - Islam Nassar; Munawar Hayat; Ehsan Abbasnejad; Hamid Rezatofighi; Gholamreza Haffari (CVPR, 2023)

Energy-based Self-Training and Normalization for Unsupervised Domain Adaptation. - Samitha Herath; Basura Fernando; Ehsan Abbasnejad; Munawar Hayat; Shahram Khadivi; Mehrtash Harandi; Hamid Rezatofighi; Gholamreza Haffari (ICCV, 2023)

Progressive Feature Adjustment for Semi-supervised Learning from Pretrained Models. - Hai-Ming Xu; Lingqiao Liu; Hao Chen 041; Ehsan Abbasnejad; Rafael Felix (ICCV (Workshops), 2023)

Improving Reward Estimation in Goal-Conditioned Imitation Learning with Counterfactual Data and Structural Causal Models. - Mohamed Khalil Jabri; Panagiotis Papadakis; Ehsan Abbasnejad; Gilles Coppin; Javen Shi (ICINCO (2), 2023)

RanPAC: Random Projections and Pre-trained Models for Continual Learning. - Mark D. McDonnell; Dong Gong; Amin Parvaneh; Ehsan Abbasnejad; Anton van den Hengel (NeurIPS, 2023)

ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets. - Damien Teney; Yong Lin; Seong Joon Oh; Ehsan Abbasnejad (NeurIPS, 2023)

LAVA:Label-efficient Visual Learning and Adaptation. - Islam Nassar; Munawar Hayat; Ehsan Abbasnejad; Hamid Rezatofighi; Mehrtash Harandi; Gholamreza Haffari (WACV, 2023)

Zero-shot Retrieval: Augmenting Pre-trained Models with Search Engines. - Hamed Damirchi; Cristian Rodriguez Opazo; Ehsan Abbasnejad; Damien Teney; Javen Qinfeng Shi; Stephen Gould; Anton van den Hengel (CoRR, 2023)

Unveiling Backbone Effects in CLIP: Exploring Representational Synergies and Variances. - Cristian Rodriguez Opazo; Edison Marrese-Taylor; Ehsan Abbasnejad; Hamed Damirchi; Ignacio M. De La Jara; Felipe Bravo-Marquez; Anton van den Hengel (CoRR, 2023)

Deep Metric Learning for Scalable Gait-Based Person Re-Identification Using Force Platform Data. - Kayne A. Duncanson; Simon Thwaites; David Booth; Gary Hanly; William S. P. Robertson; Ehsan Abbasnejad; Dominic Thewlis (Sensors, 2023)

On the Credibility of Backdoor Attacks Against Object Detectors in the Physical World. - Bao Gia Doan; Dang Quang Nguyen; Callum Lindquist; Paul Montague; Tamas Abraham; Olivier Y. de Vel; Seyit Camtepe; Salil S. Kanhere; Ehsan Abbasnejad; Damith C. Ranasinghe (ACSAC, 2024)

Semantic Role Labeling Guided Out-of-distribution Detection. - Jinan Zou; Maihao Guo; Yu Tian 001; Yuhao Lin; Haiyao Cao; Lingqiao Liu; Ehsan Abbasnejad; Javen Qinfeng Shi (LREC/COLING, 2024)

Neural Redshift: Random Networks are not Random Functions. - Damien Teney; Armand Mihai Nicolicioiu; Valentin Hartmann; Ehsan Abbasnejad (CVPR, 2024)

Invariant Representation Learning for Generalizable Imitation. - Mohamed Khalil Jabri; Panagiotis Papadakis; Ehsan Abbasnejad; Gilles Coppin; Javen Shi (ESANN, 2024)

Bayesian Learned Models Can Detect Adversarial Malware for Free. - Bao Gia Doan; Dang Quang Nguyen; Paul Montague; Tamas Abraham; Olivier Y. de Vel; Seyit Camtepe; Salil S. Kanhere; Ehsan Abbasnejad; Damith C. Ranasinghe (ESORICS (1), 2024)

Brusleattack: a Query-Efficient Score- based Black-Box Sparse Adversarial Attack. - Viet Quoc Vo; Ehsan Abbasnejad; Damith Ranasinghe (ICLR, 2024)

Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup. - Damien Teney; Jindong Wang 001; Ehsan Abbasnejad (ICML, 2024)

BLURD: Benchmarking and Learning using a Unified Rendering and Diffusion Model. - Boris Repasky; Ehsan Abbasnejad; Anthony R. Dick (NeurIPS, 2024)

Knowledge Composition using Task Vectors with Learned Anisotropic Scaling. - Frederic Z. Zhang; Paul Albert; Cristian Rodriguez Opazo; Anton van den Hengel; Ehsan Abbasnejad (NeurIPS, 2024)

Premonition: Using Generative Models to Preempt Future Data Changes in Continual Learning. - Mark D. McDonnell; Dong Gong; Ehsan Abbasnejad; Anton van den Hengel (CoRR, 2024)

Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks. - Bao Gia Doan; Afshar Shamsi; Xiao-Yu Guo; Arash Mohammadi 001; Hamid Alinejad-Rokny; Dino Sejdinovic; Damith C. Ranasinghe; Ehsan Abbasnejad (CoRR, 2024)

Rethinking State Disentanglement in Causal Reinforcement Learning. - Haiyao Cao; Zhen Zhang 008; Panpan Cai; Yuhang Liu 002; Jinan Zou; Ehsan Abbasnejad; Biwei Huang; Mingming Gong; Anton van den Hengel; Javen Qinfeng Shi (CoRR, 2024)

ETAGE: Enhanced Test Time Adaptation with Integrated Entropy and Gradient Norms for Robust Model Performance. - Afshar Shamsi; Rejisa Becirovic; Ahmadreza Argha; Ehsan Abbasnejad; Hamid Alinejad-Rokny; Arash Mohammadi 001 (CoRR, 2024)

InvariantStock: Learning Invariant Features for Mastering the Shifting Market. - Haiyao Cao; Jinan Zou; Yuhang Liu 002; Zhen Zhang 008; Ehsan Abbasnejad; Anton van den Hengel; Javen Qinfeng Shi (Trans. Mach. Learn. Res., 2024)

Bayesian Low-Rank Learning (Bella): A Practical Approach to Bayesian Neural Networks. - Bao Gia Doan; Afshar Shamsi; Xiao-Yu Guo; Arash Mohammadi 001; Hamid Alinejad-Rokny; Dino Sejdinovic; Damien Teney; Damith C. Ranasinghe; Ehsan Abbasnejad (AAAI, 2025)

Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild. - Damien Teney; Liangze Jiang; Florin Gogianu; Ehsan Abbasnejad (CVPR, 2025)

RandLoRA: Full rank parameter-efficient fine-tuning of large models. - Paul Albert; Frederic Z. Zhang; Hemanth Saratchandran; Cristian Rodriguez Opazo; Anton van den Hengel; Ehsan Abbasnejad (ICLR, 2025)

Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling. - Cristian Rodriguez Opazo; Ehsan Abbasnejad; Damien Teney; Hamed Damirchi; Edison Marrese-Taylor; Anton van den Hengel (ICLR, 2025)

Do Deep Neural Network Solutions Form a Star Domain? - Ankit Sonthalia; Alexander Rubinstein 002; Ehsan Abbasnejad; Seong Joon Oh (ICLR, 2025)

Learning to Reason and Navigate: Parameter Efficient Action Planning with Large Language Models. - Bahram Mohammadi; Ehsan Abbasnejad; Yuankai Qi; Qi Wu 001; Anton van den Hengel; Javen Qinfeng Shi (CoRR, 2025)

Towards Higher Effective Rank in Parameter-efficient Fine-tuning using Khatri-Rao Product. - Paul Albert; Frederic Z. Zhang; Hemanth Saratchandran; Anton van den Hengel; Ehsan Abbasnejad (CoRR, 2025)

Graph spectral purification for backdoor defence in graph neural networks. - Shuiqiao Yang; Bao Gia Doan; Paul Montague; Olivier Y. de Vel; Tamas Abraham; Alsharif Abuadbba; Ehsan Abbasnejad; Seyit Camtepe; Damith C. Ranasinghe; Salil S. Kanhere (World Wide Web (WWW), 2025)