| 2026 | AAAI | Probabilities Are All You Need: A Probability-Only Approach to Uncertainty Estimation in Large Language Models. | Manh Nguyen, Sunil Gupta, Hung Le |
| 2025 | AISTATS | High Dimensional Bayesian Optimization using Lasso Variable Selection. | Vu Viet Hoang, Hung The Tran, Sunil Gupta, Vu Nguyen |
| 2025 | ECAI | DmC: Nearest Neighbor Guidance Diffusion Model for Offline Cross-Domain Reinforcement Learning. | Linh Le Pham Van, Minh Hoang Nguyen, Duc Kieu, Hung Le, Hung The Tran, Sunil Gupta |
| 2025 | ICDM | Score-Based Integrated Gradient for Root Cause Explanations of Outliers. | Phuoc Nguyen, Truyen Tran, Sunil Gupta, Svetha Venkatesh |
| 2025 | ICDM | Federated Domain Generalization with Latent Space Inversion. | Ragja Palakkadavath, Hung Le, Thanh Nguyen-Tang, Svetha Venkatesh, Sunil Gupta |
| 2025 | ICLR | Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning. | Hung Le, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh |
| 2025 | ICLR | Causal Discovery via Bayesian Optimization. | Bao Duong, Sunil Gupta, Thin Nguyen |
| 2025 | IJCAI | Navigating Social Dilemmas with LLM-based Agents via Consideration of Future Consequences. | Dung Nguyen, Hung Le, Kien Do, Sunil Gupta, Svetha Venkatesh, Truyen Tran |
| 2025 | IJCAI | Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer. | Minh Hoang Nguyen, Linh Le Pham Van, Thommen George Karimpanal, Sunil Gupta, Hung Le |
| 2025 | PAKDD | Defense Against Multi-target Multi-trigger Backdoor Attacks. | Haripriya Harikumar, Santu Rana, Kien Do, Sunil Gupta, Wei Zong, Willy Susilo, Svetha Venkatesh |
| 2025 | WACV | EvoCL: Continual Learning over Evolving Domains. | Vishnuprasadh Kumaravelu, P. K. Srijith, Sunil Gupta |
| 2025 | WACV | Fair Domain Generalization with Heterogeneous Sensitive Attributes Across Domains. | Ragja Palakkadavath, Hung Le, Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh |
| 2025 | UAI | Black-box Optimization with Unknown Constraints via Overparameterized Deep Neural Networks. | Dat Phan-Trong, Hung The Tran, Sunil Gupta |
| 2024 | AAAI | Root Cause Explanation of Outliers under Noisy Mechanisms. | Phuoc Nguyen, Truyen Tran, Sunil Gupta, Thin Nguyen, Svetha Venkatesh |
| 2024 | ACCV | Revisiting Sample Weights Based Method for Noisy-Label Detection and Classification. | Tuan Hoang, Hung Tran, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2024 | ACML | Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior. | Giang Ngo, Dang Nguyen, Sunil Gupta |
| 2024 | ICDM | Generating Realistic Tabular Data with Large Language Models. | Dang Nguyen, Sunil Gupta, Kien Do, Thin Nguyen, Svetha Venkatesh |
| 2024 | IJCAI | Diversifying Training Pool Predictability for Zero-shot Coordination: A Theory of Mind Approach. | Dung Nguyen, Hung Le, Kien Do, Sunil Gupta, Svetha Venkatesh, Truyen Tran |
| 2024 | IJCAI | EMOTE: An Explainable Architecture for Modelling the Other through Empathy. | Manisha Senadeera, Thommen Karimpanal George, Stephan Jacobs, Sunil Gupta, Santu Rana |
| 2024 | WACV | Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection. | Tuan Hoang, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2023 | AAAI | On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. | Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora |
| 2023 | ACML | Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee. | Giang Ngo, Dang Nguyen, Dat Phan-Trong, Sunil Gupta |
| 2023 | ACML | Domain Generalization with Interpolation Robustness. | Ragja Palakkadavath, Thanh Nguyen-Tang, Hung Le, Svetha Venkatesh, Sunil Gupta |
| 2023 | ICCV | Multi-weather Image Restoration via Domain Translation. | Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh, Subrahmanyam Murala |
| 2023 | ICML | Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. | Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2023 | WACV | Continual Learning with Dependency Preserving Hypernetworks. | Dupati Srikar Chandra, Sakshi Varshney, P. K. Srijith, Sunil Gupta |
| 2023 | WACV | Guiding Visual Question Answering with Attention Priors. | Thao Minh Le, Vuong Le, Sunil Gupta, Svetha Venkatesh, Truyen Tran |
| 2022 | AAAI | TRF: Learning Kernels with Tuned Random Features. | Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh |
| 2022 | AISTATS | Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. | Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2022 | ECCV | Black-Box Few-Shot Knowledge Distillation. | Dang Nguyen, Sunil Gupta, Kien Do, Svetha Venkatesh |
| 2022 | ECCV | Video Restoration Framework and Its Meta-adaptations to Data-Poor Conditions. | Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2022 | ICLR | Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. | Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh |
| 2022 | PAKDD | Real-Time Skill Discovery in Intelligent Virtual Assistants. | Preeti Gopal, Sunil Gupta, Santu Rana, Vuong Le, Trong Nguyen, Svetha Venkatesh |
| 2021 | AAAI | High Dimensional Level Set Estimation with Bayesian Neural Network. | Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2021 | AAAI | Distributional Reinforcement Learning via Moment Matching. | Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh |
| 2021 | ICML | A New Representation of Successor Features for Transfer across Dissimilar Environments. | Majid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2021 | ICML | Bayesian Optimistic Optimisation with Exponentially Decaying Regret. | Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2021 | PAKDD | Sparse Spectrum Gaussian Process for Bayesian Optimization. | Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2021 | SMC | Game based User Interface to Help Dementia Patients Improve their Cognitive and Physical Abilities. | Atluri Nikhitha Chowdhary, Nishtha Phutela, Sunil Gupta, Goldie Gabrani |
| 2020 | AAAI | Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. | Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh |
| 2020 | AAAI | Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. | Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2020 | AISTATS | Distributionally Robust Bayesian Quadrature Optimization. | Thanh Tang Nguyen, Sunil Gupta, Huong Ha, Santu Rana, Svetha Venkatesh |
| 2020 | AISTATS | Accelerated Bayesian Optimisation through Weight-Prior Tuning. | Alistair Shilton, Sunil Gupta, Santu Rana, Pratibha Vellanki, Cheng Li, Svetha Venkatesh, Laurence Park, Alessandra Sutti, David Rubin, Thomas Dorin, Alireza Vahid, Murray Height, Teo Slezak |
| 2020 | ICML | DeepCoDA: personalized interpretability for compositional health data. | Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2020 | ICPR | Factor Screening using Bayesian Active Learning and Gaussian Process Meta-Modelling. | Cheng Li, Santu Rana, Andrew Gill, Dang Nguyen, Sunil Gupta, Svetha Venkatesh |
| 2020 | IJCAI | Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. | Julian Berk, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2020 | IJCNN | Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. | Thommen George Karimpanal, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh |
| 2020 | PAKDD | Level Set Estimation with Search Space Warping. | Manisha Senadeera, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2019 | AAAI | Bayesian Functional Optimisation with Shape Prior. | Pratibha Vellanki, Santu Rana, Sunil Gupta, David Rubin de Celis Leal, Alessandra Sutti, Murray Height, Svetha Venkatesh |
| 2019 | ICDM | Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. | Vu Nguyen, Sunil Gupta, Santu Rana, My T. Thai, Cheng Li, Svetha Venkatesh |
| 2019 | PRICAI | Explaining Black-Box Models Using Interpretable Surrogates. | Deepthi Praveenlal Kuttichira, Sunil Gupta, Cheng Li, Santu Rana, Svetha Venkatesh |
| 2019 | SDM | Incomplete Conditional Density Estimation for Fast Materials Discovery. | Phuoc Nguyen, Truyen Tran, Sunil Gupta, Santu Rana, Matthew Barnett, Svetha Venkatesh |
| 2018 | AISTATS | Exploiting Strategy-Space Diversity for Batch Bayesian Optimization. | Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh |
| 2018 | ICDM | Accelerating Experimental Design by Incorporating Experimenter Hunches. | Cheng Li, Santu Rana, Sunil Gupta, Vu Nguyen, Svetha Venkatesh, Alessandra Sutti, David Rubin de Celis Leal, Teo Slezak, Murray Height, Mazher Mohammed, Ian Gibson |
| 2018 | ICDM | Differentially Private Prescriptive Analytics. | Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh |
| 2018 | ICPR | Expected Hypervolume Improvement with Constraints. | Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2018 | PAKDD | Prescriptive Analytics Through Constrained Bayesian Optimization. | Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, Svetha Venkatesh |
| 2018 | PAKDD | A Privacy Preserving Bayesian Optimization with High Efficiency. | Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2018 | PRICAI | Selecting Optimal Source for Transfer Learning in Bayesian Optimisation. | Anil Ramachandran, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2018 | PRICAI | Efficient Bayesian Optimisation Using Derivative Meta-model. | Ang Yang, Cheng Li, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2018 | UAI | Multi-Target Optimisation via Bayesian Optimisation and Linear Programming. | Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2017 | ACML | Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. | Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh |
| 2017 | AISTATS | Regret Bounds for Transfer Learning in Bayesian Optimisation. | Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2017 | ICDM | Bayesian Optimization in Weakly Specified Search Space. | Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh |
| 2017 | ICML | High Dimensional Bayesian Optimization with Elastic Gaussian Process. | Santu Rana, Cheng Li, Sunil Gupta, Vu Nguyen, Svetha Venkatesh |
| 2017 | IJCAI | High Dimensional Bayesian Optimization using Dropout. | Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton |
| 2017 | PAKDD | Stable Bayesian Optimization. | Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2016 | ACML | A Bayesian Nonparametric Approach for Multi-label Classification. | Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li, Svetha Venkatesh |
| 2016 | ADMA | Understanding Behavioral Differences Between Short and Long-Term Drinking Abstainers from Social Media. | Haripriya Harikumar, Thin Nguyen, Sunil Gupta, Santu Rana, Ramachandra Kaimal, Svetha Venkatesh |
| 2016 | ADMA | Extracting Key Challenges in Achieving Sobriety Through Shared Subspace Learning. | Haripriya Harikumar, Thin Nguyen, Santu Rana, Sunil Gupta, Ramachandra Kaimal, Svetha Venkatesh |
| 2016 | ICPR | Hyperparameter tuning for big data using Bayesian optimisation. | Tinu Theckel Joy, Santu Rana, Sunil Gupta, Svetha Venkatesh |
| 2016 | ICPR | Stable clinical prediction using graph support vector machines. | Iman Kamkar, Sunil Gupta, Cheng Li, Dinh Q. Phung, Svetha Venkatesh |
| 2016 | ICPR | Multiple adverse effects prediction in longitudinal cancer treatment. | Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, David Ashely, Trish Livingston |
| 2016 | ICPR | Transfer learning for rare cancer problems via Discriminative Sparse Gaussian Graphical model. | Budhaditya Saha, Sunil Gupta, Dinh Q. Phung, Svetha Venkatesh |
| 2016 | ICPR | Bayesian nonparametric Multiple Instance Regression. | Saravanan Subramanian, Santu Rana, Sunil Gupta, Palaniappan Bagavathi Sivakumar, C. Shunmuga Velayutham, Svetha Venkatesh |
| 2016 | PAKDD | Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework. | Cheng Li, Sunil Gupta, Santu Rana, Wei Luo, Svetha Venkatesh, David Ashely, Dinh Q. Phung |
| 2016 | PAKDD | Privacy Aware K-Means Clustering with High Utility. | Thanh Dai Nguyen, Sunil Gupta, Santu Rana, Svetha Venkatesh |
| 2015 | DSAA | Improved risk predictions via sparse imputation of patient conditions in electronic medical records. | Budhaditya Saha, Sunil Gupta, Svetha Venkatesh |
| 2015 | SDM | What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships. | Sunil Gupta, Santu Rana, Dinh Q. Phung, Svetha Venkatesh |
| 2014 | ICPR | A Bayesian Nonparametric Framework for Activity Recognition Using Accelerometer Data. | Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung |
| 2014 | PERCOM | Fixed-lag particle filter for continuous context discovery using Indian Buffet Process. | Nguyen Cong Thuong, Sunil Gupta, Svetha Venkatesh, Dinh Q. Phung |
| 2013 | PERCOM | Extraction of latent patterns and contexts from social honest signals using hierarchical Dirichlet processes. | Nguyen Cong Thuong, Dinh Q. Phung, Sunil Gupta, Svetha Venkatesh |
| 1991 | ICRA | Closed-loop control of manipulators with redundant joints using the Hamilton-Jacobi-Bellman equation. | Sunil Gupta, J. Y. S. Luh |