Recognising faces in unseen modes: A tensor based approach. - Santu Rana; Wanquan Liu; Mihai M. Lazarescu; Svetha Venkatesh (CVPR, 2008)

Efficient tensor based face recognition. - Santu Rana; Wanquan Liu; Mihai M. Lazarescu; Svetha Venkatesh (ICPR, 2008)

A unified tensor framework for face recognition. - Santu Rana; Wanquan Liu; Mihai M. Lazarescu; Svetha Venkatesh (Pattern Recognit., 2009)

Multi-modal abnormality detection in video with unknown data segmentation. - Tien-Vu Nguyen; Dinh Q. Phung; Santu Rana; Duc-Son Pham 001; Svetha Venkatesh (ICPR, 2012)

Large-scale statistical modeling of motion patterns: a Bayesian nonparametric approach. - Santu Rana; Dinh Q. Phung; Sonny Pham; Svetha Venkatesh (ICVGIP, 2012)

Exploiting side information in distance dependent Chinese restaurant processes for data clustering. - Cheng Li 003; Dinh Q. Phung; Santu Rana; Svetha Venkatesh (ICME, 2013)

Split-Merge Augmented Gibbs Sampling for Hierarchical Dirichlet Processes. - Santu Rana; Dinh Q. Phung; Svetha Venkatesh (PAKDD (2), 2013)

Regularizing Topic Discovery in EMRs with Side Information by Using Hierarchical Bayesian Models. - Cheng Li 003; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (ICPR, 2014)

Intervention-Driven Predictive Framework for Modeling Healthcare Data. - Santu Rana; Sunil Kumar Gupta 001; Dinh Q. Phung; Svetha Venkatesh (PAKDD (1), 2014)

Keeping up with Innovation: A Predictive Framework for Modeling Healthcare Data with Evolving Clinical Interventions. - Sunil Kumar Gupta 001; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (SDM, 2014)

A framework for feature extraction from hospital medical data with applications in risk prediction. - Truyen Tran 001; Wei Luo 001; Dinh Q. Phung; Sunil Gupta 001; Santu Rana; Richard Kennedy; Ann Larkins; Svetha Venkatesh (BMC Bioinform., 2014)

Differentially Private Random Forest with High Utility. - Santu Rana; Sunil Kumar Gupta 001; Svetha Venkatesh (ICDM, 2015)

Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning. - Sunil Kumar Gupta 001; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (PAKDD (1), 2015)

Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints. - Cheng Li 003; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (PAKDD (2), 2015)

What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships. - Sunil Gupta 001; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (SDM, 2015)

A predictive framework for modeling healthcare data with evolving clinical interventions. - Santu Rana; Sunil Gupta 001; Dinh Q. Phung; Svetha Venkatesh (Stat. Anal. Data Min., 2015)

A Bayesian Nonparametric Approach for Multi-label Classification. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ACML, 2016)

Understanding Behavioral Differences Between Short and Long-Term Drinking Abstainers from Social Media. - Haripriya Harikumar; Thin Nguyen; Sunil Gupta 001; Santu Rana; Ramachandra Kaimal; Svetha Venkatesh (ADMA, 2016)

Extracting Key Challenges in Achieving Sobriety Through Shared Subspace Learning. - Haripriya Harikumar; Thin Nguyen; Santu Rana; Sunil Gupta 001; Ramachandra Kaimal; Svetha Venkatesh (ADMA, 2016)

Cascade Bayesian Optimization. - Thanh Dai Nguyen; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; Kyle J. Deane; Paul G. Sanders (Australasian Conference on Artificial Intelligence, 2016)

Budgeted Batch Bayesian Optimization. - Vu Nguyen 001; Santu Rana; Sunil Kumar Gupta 001; Cheng Li 003; Svetha Venkatesh (ICDM, 2016)

Hyperparameter tuning for big data using Bayesian optimisation. - Tinu Theckel Joy; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (ICPR, 2016)

Multiple adverse effects prediction in longitudinal cancer treatment. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; David Ashely; Trish Livingston (ICPR, 2016)

Bayesian nonparametric Multiple Instance Regression. - Saravanan Subramanian; Santu Rana; Sunil Gupta 001; Palaniappan Bagavathi Sivakumar; C. Shunmuga Velayutham; Svetha Venkatesh (ICPR, 2016)

Differentially Private Multi-task Learning. - Sunil Kumar Gupta 001; Santu Rana; Svetha Venkatesh (PAISI, 2016)

Flexible Transfer Learning Framework for Bayesian Optimisation. - Tinu Theckel Joy; Santu Rana; Sunil Kumar Gupta 001; Svetha Venkatesh (PAKDD (1), 2016)

Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Wei Luo 001; Svetha Venkatesh; David Ashely; Dinh Q. Phung (PAKDD (1), 2016)

Privacy Aware K-Means Clustering with High Utility. - Thanh Dai Nguyen; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (PAKDD (2), 2016)

A new transfer learning framework with application to model-agnostic multi-task learning. - Sunil Gupta 001; Santu Rana; Budhaditya Saha; Dinh Q. Phung; Svetha Venkatesh (Knowl. Inf. Syst., 2016)

Data clustering using side information dependent Chinese restaurant processes. - Cheng Li 003; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (Knowl. Inf. Syst., 2016)

Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records. - Cheng Li 003; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (Knowl. Based Syst., 2016)

Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ACML, 2017)

Regret Bounds for Transfer Learning in Bayesian Optimisation. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (AISTATS, 2017)

Bayesian Optimization in Weakly Specified Search Space. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ICDM, 2017)

High Dimensional Bayesian Optimization with Elastic Gaussian Process. - Santu Rana; Cheng Li 003; Sunil Gupta 001; Vu Nguyen 001; Svetha Venkatesh (ICML, 2017)

High Dimensional Bayesian Optimization using Dropout. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; Alistair Shilton (IJCAI, 2017)

Process-constrained batch Bayesian optimisation. - Pratibha Vellanki; Santu Rana; Sunil Gupta 001; David Rubin; Alessandra Sutti; Thomas Dorin; Murray Height; Paul G. Sanders; Svetha Venkatesh (NIPS, 2017)

Budgeted Batch Bayesian Optimization With Unknown Batch Sizes. - Vu Nguyen 001; Santu Rana; Sunil Gupta 001; Cheng Li 003; Svetha Venkatesh (CoRR, 2017)

Exploiting Strategy-Space Diversity for Batch Bayesian Optimization. - Sunil Gupta 001; Alistair Shilton; Santu Rana; Svetha Venkatesh (AISTATS, 2018)

Sparse Approximation for Gaussian Process with Derivative Observations. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2018)

Accelerating Experimental Design by Incorporating Experimenter Hunches. - Cheng Li 003; Santu Rana; Sunil Gupta 001; Vu Nguyen 001; Svetha Venkatesh; Alessandra Sutti; David Rubin de Celis Leal; Teo Slezak; Murray Height; Mazher Mohammed; Ian Gibson (ICDM, 2018)

Differentially Private Prescriptive Analytics. - Haripriya Harikumar; Santu Rana; Sunil Gupta 001; Thin Nguyen; Ramachandra Kaimal; Svetha Venkatesh (ICDM, 2018)

Expected Hypervolume Improvement with Constraints. - Majid Abdolshah; Alistair Shilton; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (ICPR, 2018)

Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation. - Shivapratap Gopakumar; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh (NeurIPS, 2018)

Prescriptive Analytics Through Constrained Bayesian Optimization. - Haripriya Harikumar; Santu Rana; Sunil Gupta 001; Thin Nguyen; Ramachandra Kaimal; Svetha Venkatesh (PAKDD (1), 2018)

A Privacy Preserving Bayesian Optimization with High Efficiency. - Thanh Dai Nguyen; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (PAKDD (3), 2018)

Exploration Enhanced Expected Improvement for Bayesian Optimization. - Julian Berk; Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ECML/PKDD (2), 2018)

Information-Theoretic Transfer Learning Framework for Bayesian Optimisation. - Anil Ramachandran; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ECML/PKDD (2), 2018)

Selecting Optimal Source for Transfer Learning in Bayesian Optimisation. - Anil Ramachandran; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (PRICAI (1), 2018)

Efficient Bayesian Optimisation Using Derivative Meta-model. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (PRICAI, 2018)

Multi-Target Optimisation via Bayesian Optimisation and Linear Programming. - Alistair Shilton; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (UAI, 2018)

Kernel Pre-Training in Feature Space via m-Kernels. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Pratibha Vellanki; Cheng Li 003; Svetha Venkatesh; Laurence Park 001; Alessandra Sutti; David Rubin; Thomas Dorin; Alireza Vahid; Murray Height; et al. (CoRR, 2018)

Practical Batch Bayesian Optimization for Less Expensive Functions. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (CoRR, 2018)

Hybrid Generative-Discriminative Models for Inverse Materials Design. - Phuoc Nguyen; Truyen Tran 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2018)

Stable Bayesian optimization. - Thanh Dai Nguyen; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (Int. J. Data Sci. Anal., 2018)

Bayesian Functional Optimisation with Shape Prior. - Pratibha Vellanki; Santu Rana; Sunil Gupta 001; David Rubin de Celis Leal; Alessandra Sutti; Murray Height; Svetha Venkatesh (AAAI, 2019)

Bayesian Optimisation for Objective Functions with Varying Smoothness. - A. V. Arun Kumar; Santu Rana; Cheng Li 001; Sunil Gupta 001; Alistair Shilton; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2019)

Detection of Compromised Models Using Bayesian Optimization. - Deepthi Praveenlal Kuttichira; Sunil Gupta 001; Dang Nguyen 002; Santu Rana; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2019)

Bayesian Optimization with Discrete Variables. - Phuc Luong; Sunil Gupta 001; Dang Nguyen 002; Santu Rana; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2019)

Information-Theoretic Multi-task Learning Framework for Bayesian Optimisation. - Anil Ramachandran; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2019)

Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; My T. Thai; Cheng Li 003; Svetha Venkatesh (ICDM, 2019)

Multi-objective Bayesian optimisation with preferences over objectives. - Majid Abdolshah; Alistair Shilton; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (NeurIPS, 2019)

Bayesian Optimization with Unknown Search Space. - Huong Ha 001; Santu Rana; Sunil Gupta 001; Thanh Tang Nguyen; Hung Tran-The; Svetha Venkatesh (NeurIPS, 2019)

Explaining Black-Box Models Using Interpretable Surrogates. - Deepthi Praveenlal Kuttichira; Sunil Gupta 001; Cheng Li 003; Santu Rana; Svetha Venkatesh (PRICAI (1), 2019)

Incomplete Conditional Density Estimation for Fast Materials Discovery. - Phuoc Nguyen; Truyen Tran 001; Sunil Gupta 001; Santu Rana; Matthew Barnett; Svetha Venkatesh (SDM, 2019)

Stable Bayesian Optimisation via Direct Stability Quantification. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh; Majid Abdolshah; Dang Nguyen 002 (CoRR, 2019)

Sparse Spectrum Gaussian Process for Bayesian Optimisation. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2019)

Cost-aware Multi-objective Bayesian optimisation. - Majid Abdolshah; Alistair Shilton; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2019)

A flexible transfer learning framework for Bayesian optimization with convergence guarantee. - Tinu Theckel Joy; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (Expert Syst. Appl., 2019)

Filtering Bayesian optimization approach in weakly specified search space. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (Knowl. Inf. Syst., 2019)

Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. - Dang Nguyen 002; Sunil Gupta 001; Santu Rana; Alistair Shilton; Svetha Venkatesh (AAAI, 2020)

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (AAAI, 2020)

Distributionally Robust Bayesian Quadrature Optimization. - Thanh Tang Nguyen; Sunil Gupta 001; Huong Ha 001; Santu Rana; Svetha Venkatesh (AISTATS, 2020)

Accelerated Bayesian Optimisation through Weight-Prior Tuning. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Pratibha Vellanki; Cheng Li 003; Svetha Venkatesh; Laurence Park 001; Alessandra Sutti; David Rubin; Thomas Dorin; Alireza Vahid; Murray Height; et al. (AISTATS, 2020)

DeepCoDA: personalized interpretability for compositional health data. - Thomas P. Quinn; Dang Nguyen 002; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (ICML, 2020)

Factor Screening using Bayesian Active Learning and Gaussian Process Meta-Modelling. - Cheng Li 003; Santu Rana; Andrew Gill; Dang Nguyen 002; Sunil Gupta 001; Svetha Venkatesh (ICPR, 2020)

Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. - Julian Berk; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (IJCAI, 2020)

Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. - Thommen George Karimpanal; Santu Rana; Sunil Gupta 001; Truyen Tran 001; Svetha Venkatesh (IJCNN, 2020)

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Huong Ha 001; Svetha Venkatesh (NeurIPS, 2020)

Level Set Estimation with Search Space Warping. - Manisha Senadeera; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (PAKDD (2), 2020)

Scalable Backdoor Detection in Neural Networks. - Haripriya Harikumar; Vuong Le; Santu Rana; Sourangshu Bhattacharya; Sunil Gupta 001; Svetha Venkatesh (ECML/PKDD (2), 2020)

Bayesian Optimization with Missing Inputs. - Phuc Luong; Dang Nguyen 002; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ECML/PKDD (2), 2020)

Unsupervised Anomaly Detection on Temporal Multiway Data. - Duc Nguyen; Phuoc Nguyen; Kien Do; Santu Rana; Sunil Gupta 001; Truyen Tran 001 (SSCI, 2020)

Bayesian Optimization for Adaptive Experimental Design: A Review. - Stewart Greenhill; Santu Rana; Sunil Gupta 001; Pratibha Vellanki; Svetha Venkatesh (IEEE Access, 2020)

Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Antonio Robles-Kelly; Svetha Venkatesh (CoRR, 2020)

HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network. - Phuoc Nguyen; Truyen Tran 001; Sunil Gupta 001; Santu Rana; Hieu-Chi Dam; Svetha Venkatesh (CoRR, 2020)

Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2020)

Logically Consistent Loss for Visual Question Answering. - Anh-Cat Le-Ngo; Truyen Tran 001; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2020)

Bayesian optimisation in unknown bounded search domains. - Julian Berk; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh (Knowl. Based Syst., 2020)

Batch Bayesian optimization using multi-scale search. - Tinu Theckel Joy; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (Knowl. Based Syst., 2020)

Fast hyperparameter tuning using Bayesian optimization with directional derivatives. - Tinu Theckel Joy; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (Knowl. Based Syst., 2020)

Incorporating expert prior in Bayesian optimisation via space warping. - Anil Ramachandran; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (Knowl. Based Syst., 2020)

Bayesian strategy selection identifies optimal solutions to complex problems using an example from GP prescribing. - Steven Allender; Joshua Hayward; Sunil Gupta 001; A. Sanigorski; Santu Rana; Hugh Seward; Stephan Jacobs; Svetha Venkatesh (npj Digit. Medicine, 2020)

High Dimensional Level Set Estimation with Bayesian Neural Network. - Huong Ha 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (AAAI, 2021)

A New Representation of Successor Features for Transfer across Dissimilar Environments. - Majid Abdolshah; Hung Le 002; Thommen George Karimpanal; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ICML, 2021)

Bayesian Optimistic Optimisation with Exponentially Decaying Regret. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ICML, 2021)

Targeted Universal Adversarial Perturbations for Automatic Speech Recognition. - Wei Zong; Yang-Wai Chow; Willy Susilo; Santu Rana; Svetha Venkatesh (ISC, 2021)

Kernel Functional Optimisation. - Arun Kumar Anjanapura Venkatesh; Alistair Shilton; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (NeurIPS, 2021)

Sparse Spectrum Gaussian Process for Bayesian Optimization. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (PAKDD (2), 2021)

Knowledge Distillation with Distribution Mismatch. - Dang Nguyen 002; Sunil Gupta 001; Trong Nguyen; Santu Rana; Phuoc Nguyen; Truyen Tran 001; Ky Le; Shannon Ryan; Svetha Venkatesh (ECML/PKDD (2), 2021)

Variational Hyper-encoding Networks. - Phuoc Nguyen; Truyen Tran 001; Sunil Gupta 001; Santu Rana; Hieu-Chi Dam; Svetha Venkatesh (ECML/PKDD (2), 2021)

Fast Conditional Network Compression Using Bayesian HyperNetworks. - Phuoc Nguyen; Truyen Tran 001; Ky Le; Sunil Gupta 001; Santu Rana; Dang Nguyen 002; Trong Nguyen; Shannon Ryan; Svetha Venkatesh (ECML/PKDD (3), 2021)

Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient. - Haripriya Harikumar; Thomas P. Quinn; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (BioData Min., 2021)

ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms. - Huong Ha 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2021)

Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support. - Hung Tran-The; Sunil Gupta 001; Thanh Nguyen-Tang; Santu Rana; Svetha Venkatesh (CoRR, 2021)

Plug and Play, Model-Based Reinforcement Learning. - Majid Abdolshah; Hung Le 002; Thommen George Karimpanal; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2021)

Semantic Host-free Trojan Attack. - Haripriya Harikumar; Kien Do; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2021)

Fairness improvement for black-box classifiers with Gaussian process. - Dang Nguyen 002; Sunil Gupta 001; Santu Rana; Alistair Shilton; Svetha Venkatesh (Inf. Sci., 2021)

Adaptive cost-aware Bayesian optimization. - Phuc Luong; Dang Nguyen 002; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (Knowl. Based Syst., 2021)

TRF: Learning Kernels with Tuned Random Features. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Arun Kumar Anjanapura Venkatesh; Svetha Venkatesh (AAAI, 2022)

Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (AISTATS, 2022)

Sympathy-based Reinforcement Learning Agents. - Manisha Senadeera; Thommen George Karimpanal; Sunil Gupta 001; Santu Rana (AAMAS, 2022)

Towards Effective and Robust Neural Trojan Defenses via Input Filtering. - Kien Do; Haripriya Harikumar; Hung Le 002; Dung Nguyen 001; Truyen Tran 001; Santu Rana; Dang Nguyen 002; Willy Susilo; Svetha Venkatesh (ECCV (5), 2022)

Video Restoration Framework and Its Meta-adaptations to Data-Poor Conditions. - Prashant W. Patil; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ECCV (28), 2022)

Fast Model-based Policy Search for Universal Policy Networks. - Buddhika Laknath Semage; Thommen George Karimpanal; Santu Rana; Svetha Venkatesh (ICPR, 2022)

Uncertainty Aware System Identification with Universal Policies. - Buddhika Laknath Semage; Thommen George Karimpanal; Santu Rana; Svetha Venkatesh (ICPR, 2022)

Intuitive Physics Guided Exploration for Sample Efficient Sim2real Transfer. - Buddhika Laknath Semage; Thommen George Karimpanal; Santu Rana; Svetha Venkatesh (ICPR Workshops (2), 2022)

Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation. - Kien Do; Hung Le 002; Dung Nguyen 001; Dang Nguyen 002; Haripriya Harikumar; Truyen Tran 001; Santu Rana; Svetha Venkatesh (NeurIPS, 2022)

Expected Improvement for Contextual Bandits. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Tuan Truong; Long Tran-Thanh; Svetha Venkatesh (NeurIPS, 2022)

Human-AI Collaborative Bayesian Optimisation. - Arun Kumar A. V.; Santu Rana; Alistair Shilton; Svetha Venkatesh (NeurIPS, 2022)

Real-Time Skill Discovery in Intelligent Virtual Assistants. - Preeti Gopal; Sunil Gupta 001; Santu Rana; Vuong Le; Trong Nguyen; Svetha Venkatesh (PAKDD (1), 2022)

Defense Against Multi-target Trojan Attacks. - Haripriya Harikumar; Santu Rana; Kien Do; Sunil Gupta 001; Wei Zong; Willy Susilo; Svetha Venkatesh (CoRR, 2022)

Prescriptive analytics with differential privacy. - Haripriya Harikumar; Santu Rana; Sunil Gupta 001; Thin Nguyen; Ramachandra Kaimal; Svetha Venkatesh (Int. J. Data Sci. Anal., 2022)

Verification of integrity of deployed deep learning models using Bayesian Optimization. - Deepthi Praveenlal Kuttichira; Sunil Gupta 001; Dang Nguyen 002; Santu Rana; Svetha Venkatesh (Knowl. Based Syst., 2022)

Dual-frame spatio-temporal feature modulation for video enhancement. - Prashant W. Patil; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (Pattern Recognit., 2022)

Controlled Diversity with Preference : Towards Learning a Diverse Set of Desired Skills. - Maxence Hussonnois; Thommen George Karimpanal; Santu Rana (AAMAS, 2023)

Multi-weather Image Restoration via Domain Translation. - Prashant W. Patil; Sunil Gupta 001; Santu Rana; Svetha Venkatesh; Subrahmanyam Murala (ICCV, 2023)

Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ICML, 2023)

Gradient Descent in Neural Networks as Sequential Learning in RKBS. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2023)

Zero-shot Sim2Real Adaptation Across Environments. - Buddhika Laknath Semage; Thommen George Karimpanal; Santu Rana; Svetha Venkatesh (CoRR, 2023)

BO-Muse: A human expert and AI teaming framework for accelerated experimental design. - Sunil Gupta 001; Alistair Shilton; Arun Kumar A. V.; Shannon Ryan; Majid Abdolshah; Hung Le 002; Santu Rana; Julian Berk; Mahad Rashid; Svetha Venkatesh (CoRR, 2023)

LearnDefend: Learning to Defend against Targeted Model-Poisoning Attacks on Federated Learning. - Kiran Purohit; Soumi Das; Sourangshu Bhattacharya; Santu Rana (CoRR, 2023)

Predictive Modeling through Hyper-Bayesian Optimization. - Manisha Senadeera; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2023)

Sample-Efficient Co-Design of Robotic Agents Using Multi-fidelity Training on Universal Policy Network. - Kishan R. Nagiredla; Buddhika Laknath Semage; Thommen George Karimpanal; Arun Kumar A. V.; Santu Rana (CoRR, 2023)

Balanced Q-learning: Combining the influence of optimistic and pessimistic targets. - Thommen George Karimpanal; Hung Le 002; Majid Abdolshah; Santu Rana; Sunil Gupta 001; Truyen Tran 001; Svetha Venkatesh (Artif. Intell., 2023)

Revisiting Sample Weights Based Method for Noisy-Label Detection and Classification. - Tuan Hoang; Hung Tran; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (ACCV (1), 2024)

ECoDe: A Sample-Efficient Method for Co-design of Robotic Agents. - Kishan R. Nagiredla; Buddhika Laknath Semage; Arun Kumar Anjanapura Venkatesh; Thommen George Karimpanal; Santu Rana (AI (2), 2024)

Revisiting the Dataset Bias Problem from a Statistical Perspective. - Kien Do; Dung Nguyen 001; Hung Le 002; Thao Le 003; Dang Nguyen 002; Haripriya Harikumar; Truyen Tran 001; Santu Rana; Svetha Venkatesh (ECAI, 2024)

A Data-Driven Defense Against Edge-Case Model Poisoning Attacks on Federated Learning. - Kiran Purohit; Soumi Das; Sourangshu Bhattacharya; Santu Rana (ECAI, 2024)

Personalisation via Dynamic Policy Fusion. - Ajsal Shereef Palattuparambil; Thommen Karimpanal George; Santu Rana (HAI, 2024)

Composite Concept Extraction Through Backdooring. - Banibrata Ghosh; Haripriya Harikumar; Khoa D. Doan; Svetha Venkatesh; Santu Rana (ICPR (29), 2024)

EMOTE: An Explainable Architecture for Modelling the Other through Empathy. - Manisha Senadeera; Thommen Karimpanal George; Stephan Jacobs; Sunil Gupta 001; Santu Rana (IJCAI, 2024)

Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. - A. V. Arun Kumar; Alistair Shilton; Sunil Gupta 001; Santu Rana; Stewart Greenhill; Svetha Venkatesh (ECML/PKDD (6), 2024)

Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection. - Tuan Hoang; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (WACV, 2024)

Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2024)

Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks. - Tri Minh Nguyen 005; Sherif Abdulkader Tawfik; Truyen Tran 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2024)

Human-Aligned Skill Discovery: Balancing Behaviour Exploration and Alignment. - Maxence Hussonnois; Thommen George Karimpanal; Santu Rana (AAMAS, 2025)

ALPACA AGAINST VICUNA: Using LLMs to Uncover Memorization of LLMs. - Aly M. Kassem; Omar Mahmoud; Niloofar Mireshghallah; Hyunwoo Kim 002; Yulia Tsvetkov; Yejin Choi 001; Sherif Saad; Santu Rana (NAACL (Long Papers), 2025)

Defense Against Multi-target Multi-trigger Backdoor Attacks. - Haripriya Harikumar; Santu Rana; Kien Do; Sunil Gupta 001; Wei Zong; Willy Susilo; Svetha Venkatesh (PAKDD (6), 2025)

Targeted Manifold Manipulation Against Adversarial Attacks. - Banibrata Ghosh; Haripriya Harikumar; Svetha Venkatesh; Santu Rana (SaTML, 2025)

Human-informed skill discovery: Controlled diversity with preference in reinforcement learning. - Maxence Hussonnois; Thommen George Karimpanal; Mayank Shekhar Jha; Santu Rana (Expert Syst. Appl., 2025)

Accelerated experimental design using a human-AI teaming framework. - Arun Kumar Anjanapura Venkatesh; Alistair Shilton; Sunil Gupta 001; Shannon Ryan; Majid Abdolshah; Hung Le 002; Santu Rana; Julian Berk; Mahad Rashid; Svetha Venkatesh (Knowl. Based Syst., 2025)

Unpaired recurrent learning for real-world video de-hazing. - Prashant W. Patil; Santosh Nagnath Randive; Sunil Gupta 001; Santu Rana; Svetha Venkatesh; Subrahmanyam Murala (Pattern Recognit., 2025)

Improving Multilingual Language Models by Aligning Representations through Steering. - Omar Mahmoud; Buddhika Laknath Semage; Thommen George Karimpanal; Santu Rana (CoRR, 2025)

MAGIK: Mapping to Analogous Goals via Imagination-enabled Knowledge Transfer. - Ajsal Shereef Palattuparambil; Thommen George Karimpanal; Santu Rana (CoRR, 2025)

TRUST: Test-time Resource Utilization for Superior Trustworthiness. - Haripriya Harikumar; Santu Rana (CoRR, 2025)

LaGR-SEQ: Language-guided reinforcement learning with sample-efficient querying. - Thommen Karimpanal George; Buddhika Laknath Semage; Santu Rana; Hung Le 002; Truyen Tran 001; Sunil Gupta 001; Svetha Venkatesh (Neural Comput. Appl., 2025)

Learning coupled Allen-Cahn and Cahn-Hilliard phase-field equations using Physics-informed neural operator(PINO). - Gaijinliu Gangmei; Santu Rana; Bernard Rolfe; Kishalay Mitra; Saswata Bhattacharyya (CoRR, 2025)