Mahsa Baktashmotlagh

120 papers A* 26A 10B 5Misc 5Journal 58Unranked 13

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	ALSA: Anchors in Logit Space for Out-of-Distribution Accuracy Estimation. CoRR Chenzhi Liu, Mahsa Baktashmotlagh, Yanran Tang, Zi Huang, Ruihong Qiu
2025	J	`jnl`	Benchmarking Transferability: A Framework for Fair and Robust Evaluation. CoRR Alireza Kazemi, Helia Rezvani, Mahsa Baktashmotlagh
2025	A	`conf`	Feature Space Perturbation: A Panacea to Enhanced Transferability Estimation. WACV Prafful Kumar Khoba, Zijian Wang, Chetan Arora, Mahsa Baktashmotlagh
2025	J	`jnl`	Feature Space Perturbation: A Panacea to Enhanced Transferability Estimation. CoRR Prafful Kumar Khoba, Zijian Wang, Chetan Arora, Mahsa Baktashmotlagh
2025	J	`jnl`	GIQ: Benchmarking 3D Geometric Reasoning of Vision Foundation Models with Simulated and Real Polyhedra. CoRR Mateusz Michalkiewicz, Anekha Sokhal, Tadeusz Michalkiewicz, Piotr Pawlikowski, Mahsa Baktashmotlagh, Varun Jampani, Guha Balakrishnan
2025	A*	`conf`	Improving Out-of-Distribution Detection via Dynamic Covariance Calibration. ICML Kaiyu Guo, Zijian Wang, Tan Pan, Brian C. Lovell, Mahsa Baktashmotlagh
2025	J	`jnl`	Improving Out-of-Distribution Detection via Dynamic Covariance Calibration. CoRR Kaiyu Guo, Zijian Wang, Tan Pan, Brian C. Lovell, Mahsa Baktashmotlagh
2025	—	`conf`	Leveraging Gradient Information for Out-of-Domain Performance Estimations. ECML/PKDD (6) Ekaterina Khramtsova, Mahsa Baktashmotlagh, Guido Zuccon, Xi Wang, Mathieu Salzmann
2025	A*	`conf`	MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection. ICLR Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh, Yonggang Zhang, Zi Huang, Yadan Luo
2025	J	`jnl`	Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization. CoRR Tan Pan, Kaiyu Guo, Dongli Xu, Zhaorui Tan, Chen Jiang, Deshu Chen, Xin Guo, Brian C. Lovell, Limei Han, Yuan Cheng, Mahsa Baktashmotlagh
2025	J	`jnl`	SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images. CoRR Kaiyu Guo, Tan Pan, Chen Jiang, Zijian Wang, Brian C. Lovell, Limei Han, Yuan Cheng, Mahsa Baktashmotlagh
2025	A*	`conf`	Shape-Space Deformer: Unified Visuo-Tactile Representations for Robotic Manipulation of Deformable Objects. ICRA Sean M. V. Collins, Brendan Tidd, Mahsa Baktashmotlagh, Peyman Moghadam
2025	—	`conf`	Spectral Distribution Alignment for Enhanced Generalization in Regression. ECML/PKDD (6) Kaiyu Guo, Zijian Wang, Brian C. Lovell, Mahsa Baktashmotlagh
2025	A*	`conf`	WisWheat: A Three-Tiered Vision-Language Dataset for Wheat Management. ACM Multimedia Bowen Yuan, Selena Song, Javier Fernandez, Yadan Luo, Mahsa Baktashmotlagh, Zijian Wang
2025	J	`jnl`	WisWheat: A Three-Tiered Vision-Language Dataset for Wheat Management. CoRR Bowen Yuan, Selena Song, Javier Fernandez, Yadan Luo, Mahsa Baktashmotlagh, Zijian Wang
2024	A*	`conf`	Color-Oriented Redundancy Reduction in Dataset Distillation. NeurIPS Bowen Yuan, Zijian Wang, Mahsa Baktashmotlagh, Yadan Luo, Zi Huang
2024	J	`jnl`	Color-Oriented Redundancy Reduction in Dataset Distillation. CoRR Bowen Yuan, Zijian Wang, Mahsa Baktashmotlagh, Yadan Luo, Zi Huang
2024	A*	`conf`	DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection. NeurIPS Jia Syuen Lim, Zhuoxiao Chen, Zhi Chen, Mahsa Baktashmotlagh, Xin Yu, Zi Huang, Yadan Luo
2024	J	`jnl`	DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection. CoRR Jia Syuen Lim, Zhuoxiao Chen, Mahsa Baktashmotlagh, Zhi Chen, Xin Yu, Zi Huang, Yadan Luo
2024	A	`conf`	Domain-Aware Knowledge Distillation for Continual Model Generalization. WACV Nikhil Reddy, Mahsa Baktashmotlagh, Chetan Arora
2024	A*	`conf`	Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection. SIGIR Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon
2024	J	`jnl`	Embark on DenseQuest: A System for Selecting the Best Dense Retriever for a Custom Collection. CoRR Ekaterina Khramtsova, Teerapong Leelanupab, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon
2024	A*	`conf`	Leveraging LLMs for Unsupervised Dense Retriever Ranking. SIGIR Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon
2024	J	`jnl`	Leveraging LLMs for Unsupervised Dense Retriever Ranking. CoRR Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Guido Zuccon
2024	J	`jnl`	MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection. CoRR Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh, Zi Huang, Yadan Luo
2024	J	`jnl`	Not all Views are Created Equal: Analyzing Viewpoint Instabilities in Vision Foundation Models. CoRR Mateusz Michalkiewicz, Sheena Bai, Mahsa Baktashmotlagh, Varun Jampani, Guha Balakrishnan
2024	J	`jnl`	Shape-Space Deformer: Unified Visuo-Tactile Representations for Robotic Manipulation of Deformable Objects. CoRR Sean M. V. Collins, Brendan Tidd, Mahsa Baktashmotlagh, Peyman Moghadam
2024	—	`conf`	Source-Free Domain-Invariant Performance Prediction. ECCV (80) Ekaterina Khramtsova, Mahsa Baktashmotlagh, Guido Zuccon, Xi Wang, Mathieu Salzmann
2024	J	`jnl`	Source-Free Domain-Invariant Performance Prediction. CoRR Ekaterina Khramtsova, Mahsa Baktashmotlagh, Guido Zuccon, Xi Wang, Mathieu Salzmann
2023	A	`conf`	Center-aware Adversarial Augmentation for Single Domain Generalization. WACV Tianle Chen, Mahsa Baktashmotlagh, Zijian Wang, Mathieu Salzmann
2023	A	`conf`	Convolutional Persistence as a Remedy to Neural Model Analysis. AISTATS Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh
2023	J	`jnl`	DI-NIDS: Domain invariant network intrusion detection system. Knowl. Based Syst. Siamak Layeghy, Mahsa Baktashmotlagh, Marius Portmann
2023	A*	`conf`	Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters. ICCV Mateusz Michalkiewicz, Masoud Faraki, Xiang Yu, Manmohan Chandraker, Mahsa Baktashmotlagh
2023	J	`jnl`	Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters. CoRR Mateusz Michalkiewicz, Masoud Faraki, Xiang Yu, Manmohan Chandraker, Mahsa Baktashmotlagh
2023	A*	`conf`	Exploring Active 3D Object Detection from a Generalization Perspective. ICLR Yadan Luo, Zhuoxiao Chen, Zijian Wang, Xin Yu, Zi Huang, Mahsa Baktashmotlagh
2023	J	`jnl`	Exploring Active 3D Object Detection from a Generalization Perspective. CoRR Yadan Luo, Zhuoxiao Chen, Zijian Wang, Xin Yu, Zi Huang, Mahsa Baktashmotlagh
2023	A	`conf`	FFM: Injecting Out-of-Domain Knowledge via Factorized Frequency Modification. WACV Zijian Wang, Yadan Luo, Zi Huang, Mahsa Baktashmotlagh
2023	A*	`conf`	How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability. ICCV Zijian Wang, Yadan Luo, Liang Zheng, Zi Huang, Mahsa Baktashmotlagh
2023	J	`jnl`	Interpretable Signed Link Prediction With Signed Infomax Hyperbolic Graph. IEEE Trans. Knowl. Data Eng. Yadan Luo, Zi Huang, Hongxu Chen, Yang Yang, Hongzhi Yin, Mahsa Baktashmotlagh
2023	J	`jnl`	KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection. CoRR Yadan Luo, Zhuoxiao Chen, Zhen Fang, Zheng Zhang, Zi Huang, Mahsa Baktashmotlagh
2023	A*	`conf`	Kecor: Kernel Coding Rate Maximization for Active 3D Object Detection. ICCV Yadan Luo, Zhuoxiao Chen, Zhen Fang, Zheng Zhang, Mahsa Baktashmotlagh, Zi Huang
2023	A*	`conf`	Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling. ICCV Zhuoxiao Chen, Yadan Luo, Zheng Wang, Mahsa Baktashmotlagh, Zi Huang
2023	J	`jnl`	Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling. CoRR Zhuoxiao Chen, Yadan Luo, Zi Huang, Zheng Wang, Mahsa Baktashmotlagh
2023	—	`conf`	Selecting which Dense Retriever to use for Zero-Shot Search. SIGIR-AP Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon
2023	J	`jnl`	Selecting which Dense Retriever to use for Zero-Shot Search. CoRR Ekaterina Khramtsova, Shengyao Zhuang, Mahsa Baktashmotlagh, Xi Wang, Guido Zuccon
2023	J	`jnl`	Source-Free Progressive Graph Learning for Open-Set Domain Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. Yadan Luo, Zijian Wang, Zhuoxiao Chen, Zi Huang, Mahsa Baktashmotlagh
2022	B	`conf`	Contrastive Class-aware Adaptation for Domain Generalization. ICPR Tianle Chen, Mahsa Baktashmotlagh, Mathieu Salzmann
2022	J	`jnl`	DI-NIDS: Domain Invariant Network Intrusion Detection System. CoRR Siamak Layeghy, Mahsa Baktashmotlagh, Marius Portmann
2022	A	`conf`	Learning to Generate the Unknowns as a Remedy to the Open-Set Domain Shift. WACV Mahsa Baktashmotlagh, Tianle Chen, Mathieu Salzmann
2022	—	`conf`	Master of All: Simultaneous Generalization of Urban-Scene Segmentation to All Adverse Weather Conditions. ECCV (39) Nikhil Reddy, Abhinav Singhal, Abhishek Kumar, Mahsa Baktashmotlagh, Chetan Arora
2022	Misc	`conf`	Modular Construction Planning Using Graph Neural Network Heuristic Search. AI Philip Hawkins, Frédéric Maire, Simon Denman, Mahsa Baktashmotlagh
2022	—	`conf`	Rethinking Persistent Homology For Visual Recognition. TAG-ML Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh
2022	J	`jnl`	Rethinking Persistent Homology for Visual Recognition. CoRR Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh
2022	J	`jnl`	Source-Free Progressive Graph Learning for Open-Set Domain Adaptation. CoRR Yadan Luo, Zijian Wang, Zhuoxiao Chen, Zi Huang, Mahsa Baktashmotlagh
2021	J	`jnl`	Closing the Gap of Simulation to Reality in Electromagnetic Imaging of Brain Strokes via Deep Neural Networks. IEEE Trans. Computational Imaging Ahmed Al-Saffar, Alina Bialkowski, Mahsa Baktashmotlagh, Adnan Trakic, Lei Guo, Amin M. Abbosh
2021	—	`conf`	Conditional Extreme Value Theory for Open Set Video Domain Adaptation. MMAsia Zhuoxiao Chen, Yadan Luo, Mahsa Baktashmotlagh
2021	J	`jnl`	Conditional Extreme Value Theory for Open Set Video Domain Adaptation. CoRR Zhuoxiao Chen, Yadan Luo, Mahsa Baktashmotlagh
2021	J	`jnl`	Going Deeper into Semi-supervised Person Re-identification. CoRR Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh
2021	A	`conf`	Keypoint-Aligned Embeddings for Image Retrieval and Re-identification. WACV Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh
2021	J	`jnl`	Learning Compositional Shape Priors for Few-Shot 3D Reconstruction. CoRR Mateusz Michalkiewicz, Stavros Tsogkas, Sarah Parisot, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky
2021	A*	`conf`	Learning to Diversify for Single Domain Generalization. ICCV Zijian Wang, Yadan Luo, Ruihong Qiu, Zi Huang, Mahsa Baktashmotlagh
2021	J	`jnl`	Learning to Diversify for Single Domain Generalization. CoRR Zijian Wang, Yadan Luo, Ruihong Qiu, Zi Huang, Mahsa Baktashmotlagh
2021	—	`conf`	Neural-Symbolic Commonsense Reasoner with Relation Predictors. ACL/IJCNLP (2) Farhad Moghimifar, Lizhen Qu, Yue Zhuo, Gholamreza Haffari, Mahsa Baktashmotlagh
2021	J	`jnl`	Neural-Symbolic Commonsense Reasoner with Relation Predictors. CoRR Farhad Moghimifar, Lizhen Qu, Yue Zhuo, Gholamreza Haffari, Mahsa Baktashmotlagh
2021	Misc	`conf`	Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant Embeddings. DICTA Olga Moskvyak, Frédéric Maire, Feras Dayoub, Asia O. Armstrong, Mahsa Baktashmotlagh
2021	A*	`conf`	Semi-supervised Keypoint Localization. ICLR Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh
2021	J	`jnl`	Semi-supervised Keypoint Localization. CoRR Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh
2020	A	`conf`	A Simple and Scalable Shape Representation for 3D Reconstruction. BMVC Mateusz Michalkiewicz, Eugene Belilovsky, Mahsa Baktashmotlagh, Anders P. Eriksson
2020	J	`jnl`	A Simple and Scalable Shape Representation for 3D Reconstruction. CoRR Mateusz Michalkiewicz, Eugene Belilovsky, Mahsa Baktashmotlagh, Anders P. Eriksson
2020	A*	`conf`	Adversarial Bipartite Graph Learning for Video Domain Adaptation. ACM Multimedia Yadan Luo, Zi Huang, Zijian Wang, Zheng Zhang, Mahsa Baktashmotlagh
2020	J	`jnl`	Adversarial Bipartite Graph Learning for Video Domain Adaptation. CoRR Yadan Luo, Zi Huang, Zijian Wang, Zheng Zhang, Mahsa Baktashmotlagh
2020	J	`jnl`	COSMO: Conditional SEQ2SEQ-based Mixture Model for Zero-Shot Commonsense Question Answering. CoRR Farhad Moghimifar, Lizhen Qu, Yue Zhuo, Mahsa Baktashmotlagh, Gholamreza Haffari
2020	J	`jnl`	Correlation-aware adversarial domain adaptation and generalization. Pattern Recognit. Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan
2020	B	`conf`	CosMo: Conditional Seq2Seq-based Mixture Model for Zero-Shot Commonsense Question Answering. COLING Farhad Moghimifar, Lizhen Qu, Yue Zhuo, Mahsa Baktashmotlagh, Gholamreza Haffari
2020	Misc	`conf`	Domain Adaptative Causality Encoder. ALTA Farhad Moghimifar, Gholamreza Haffari, Mahsa Baktashmotlagh
2020	J	`jnl`	Domain Adaptative Causality Encoder. CoRR Farhad Moghimifar, Gholamreza Haffari, Mahsa Baktashmotlagh
2020	—	`conf`	Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors. ECCV (25) Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky
2020	J	`jnl`	Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors. CoRR Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky
2020	J	`jnl`	Implicitly Defined Layers in Neural Networks. CoRR Qianggong Zhang, Yanyang Gu, Mateusz Michalkiewicz, Mahsa Baktashmotlagh, Anders P. Eriksson
2020	J	`jnl`	Interpretable Signed Link Prediction with Signed Infomax Hyperbolic Graph. CoRR Yadan Luo, Zi Huang, Hongxu Chen, Yang Yang, Mahsa Baktashmotlagh
2020	J	`jnl`	Keypoint-Aligned Embeddings for Image Retrieval and Re-identification. CoRR Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh
2020	Misc	`conf`	Learning Causal Bayesian Networks from Text. ALTA Farhad Moghimifar, Afshin Rahimi, Mahsa Baktashmotlagh, Xue Li
2020	J	`jnl`	Learning Causal Bayesian Networks from Text. CoRR Farhad Moghimifar, Afshin Rahimi, Mahsa Baktashmotlagh, Xue Li
2020	—	`conf`	Learning Landmark Guided Embeddings for Animal Re-identification. WACV Workshops Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh
2020	A*	`conf`	Learning from the Past: Continual Meta-Learning with Bayesian Graph Neural Networks. AAAI Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Mahsa Baktashmotlagh, Yang Yang
2020	J	`jnl`	Learning landmark guided embeddings for animal re-identification. CoRR Olga Moskvyak, Frédéric Maire, Feras Dayoub, Mahsa Baktashmotlagh
2020	—	`ch.`	On Minimum Discrepancy Estimation for Deep Domain Adaptation. Domain Adaptation for Visual Understanding Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan
2020	A*	`conf`	Progressive Graph Learning for Open-Set Domain Adaptation. ICML Yadan Luo, Zijian Wang, Zi Huang, Mahsa Baktashmotlagh
2020	J	`jnl`	Progressive Graph Learning for Open-Set Domain Adaptation. CoRR Yadan Luo, Zijian Wang, Zi Huang, Mahsa Baktashmotlagh
2020	A*	`conf`	Prototype-Matching Graph Network for Heterogeneous Domain Adaptation. ACM Multimedia Zijian Wang, Yadan Luo, Zi Huang, Mahsa Baktashmotlagh
2019	J	`jnl`	Correlation-aware Adversarial Domain Adaptation and Generalization. CoRR Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan
2019	J	`jnl`	Deep Level Sets: Implicit Surface Representations for 3D Shape Inference. CoRR Mateusz Michalkiewicz, Jhony K. Pontes, Dominic Jack, Mahsa Baktashmotlagh, Anders P. Eriksson
2019	A*	`conf`	Implicit Surface Representations As Layers in Neural Networks. ICCV Mateusz Michalkiewicz, Jhony Kaesemodel Pontes, Dominic Jack, Mahsa Baktashmotlagh, Anders P. Eriksson
2019	—	`conf`	Learning Factorized Representations for Open-Set Domain Adaptation. ICLR (Poster) Mahsa Baktashmotlagh, Masoud Faraki, Tom Drummond, Mathieu Salzmann
2019	J	`jnl`	Learning from the Past: Continual Meta-Learning via Bayesian Graph Modeling. CoRR Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Mahsa Baktashmotlagh, Yang Yang
2019	A	`conf`	Multi-Component Image Translation for Deep Domain Generalization. WACV Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan
2019	Misc	`conf`	Object Graph Networks for Spatial Language Grounding. DICTA Philip Hawkins, Frédéric Maire, Simon Denman, Mahsa Baktashmotlagh
2019	J	`jnl`	On Minimum Discrepancy Estimation for Deep Domain Adaptation. CoRR Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan
2019	J	`jnl`	Robust Re-identification of Manta Rays from Natural Markings by Learning Pose Invariant Embeddings. CoRR Olga Moskvyak, Frédéric Maire, Asia O. Armstrong, Feras Dayoub, Mahsa Baktashmotlagh
2019	J	`jnl`	Visualizing Student Opinion Through Text Analysis. IEEE Trans. Educ. Samuel Cunningham-Nelson, Mahsa Baktashmotlagh, Wageeh W. Boles
2018	J	`jnl`	Learning Factorized Representations for Open-set Domain Adaptation. CoRR Mahsa Baktashmotlagh, Masoud Faraki, Tom Drummond, Mathieu Salzmann
2018	J	`jnl`	Multi-component Image Translation for Deep Domain Generalization. CoRR Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan
2017	B	`conf`	Deep discovery of facial motions using a shallow embedding layer. ICIP Afsaneh Ghasemi, Mahsa Baktashmotlagh, Simon Denman, Sridha Sridharan, Dung Nguyen Tien, Clinton Fookes
2017	J	`jnl`	From Review to Rating: Exploring Dependency Measures for Text Classification. CoRR Samuel Cunningham-Nelson, Mahsa Baktashmotlagh, Wageeh W. Boles
2017	A*	`conf`	From Shared Subspaces to Shared Landmarks: A Robust Multi-Source Classification Approach. AAAI Sarah M. Erfani, Mahsa Baktashmotlagh, Masud Moshtaghi, Vinh Nguyen, Christopher Leckie, James Bailey, Kotagiri Ramamohanarao
2017	—	`ch.`	Learning Domain Invariant Embeddings by Matching Distributions. Domain Adaptation in Computer Vision Applications Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Mathieu Salzmann
2017	—	`conf`	Speaker verification with multi-run ICA based speech enhancement. ICSPCS Ahmed Kamil Hasan Al-Ali, David Dean, Bouchra Senadji, Mahsa Baktashmotlagh, Vinod Chandran
2016	J	`jnl`	Distribution-Matching Embedding for Visual Domain Adaptation. J. Mach. Learn. Res. Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Mathieu Salzmann
2016	A	`conf`	R1STM: One-class Support Tensor Machine with Randomised Kernel. SDM Sarah M. Erfani, Mahsa Baktashmotlagh, Sutharshan Rajasegarar, Vinh Nguyen, Christopher Leckie, James Bailey, Kotagiri Ramamohanarao
2016	A*	`conf`	Robust Domain Generalisation by Enforcing Distribution Invariance. IJCAI Sarah M. Erfani, Mahsa Baktashmotlagh, Masud Moshtaghi, Vinh Nguyen, Christopher Leckie, James Bailey, Kotagiri Ramamohanarao
2015	A*	`conf`	Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs. ICCV Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Mahsa Baktashmotlagh
2015	J	`jnl`	Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs. CoRR Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Mahsa Baktashmotlagh
2015	A*	`conf`	R1SVM: A Randomised Nonlinear Approach to Large-Scale Anomaly Detection. AAAI Sarah M. Erfani, Mahsa Baktashmotlagh, Sutharshan Rajasegarar, Shanika Karunasekera, Christopher Leckie
2014	J	`jnl`	Discriminative Non-Linear Stationary Subspace Analysis for Video Classification. IEEE Trans. Pattern Anal. Mach. Intell. Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Brian C. Lovell, Mathieu Salzmann
2014	A*	`conf`	Domain Adaptation on the Statistical Manifold. CVPR Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Brian C. Lovell, Mathieu Salzmann
2014	—	`—`	Learning Invariances for High-Dimensional Data Analysis Mahsa Baktashmotlagh
2013	—	`conf`	Non-Linear Stationary Subspace Analysis with Application to Video Classification. ICML (3) Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Abbas Bigdeli, Brian C. Lovell, Mathieu Salzmann
2013	A*	`conf`	Unsupervised Domain Adaptation by Domain Invariant Projection. ICCV Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Brian C. Lovell, Mathieu Salzmann
2012	B	`conf`	A wireless mesh sensor network for hazard and safety monitoring at the Port of Brisbane. LCN Amin Ahmadi, Abbas Bigdeli, Mahsa Baktashmotlagh, Brian C. Lovell
2011	B	`conf`	Dynamic resource aware sensor networks: Integration of sensor cloud and ERPs. AVSS Mahsa Baktashmotlagh, Abbas Bigdeli, Brian C. Lovell