Sunil Gupta

Probabilities Are All You Need: A Probability-Only Approach to Uncertainty Estimation in Large Language Models AAAI 2026 Fair Domain Generalization with Heterogeneous Sensitive Attributes Across Domains WACV 2025 EvoCL: Continual Learning over Evolving Domains WACV 2025 Navigating Social Dilemmas with LLM-based Agents via Consideration of Future Consequences IJCAI 2025 Black-box Optimization with Unknown Constraints via Overparameterized Deep Neural Networks UAI 2025 Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer IJCAI 2025 Causal Discovery via Bayesian Optimization ICLR 2025 Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning ICLR 2025 High Dimensional Bayesian Optimization using Lasso Variable Selection AISTATS 2025 EMOTE: An Explainable Architecture for Modelling the Other through Empathy IJCAI 2024 Learn To Unlearn for Deep Neural Networks: Minimizing Unlearning Interference With Gradient Projection WACV 2024 Diversifying Training Pool Predictability for Zero-shot Coordination: A Theory of Mind Approach IJCAI 2024 Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior ACML 2024 Root Cause Explanation of Outliers under Noisy Mechanisms AAAI 2024 Active Set Ordering NIPS 2024 Domain Generalization with Interpolation Robustness ACML 2023 On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation AAAI 2023 Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee ACML 2023 Multi-weather Image Restoration via Domain Translation ICCV 2023 Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space ICML 2023 Continual Learning With Dependency Preserving Hypernetworks WACV 2023 Guiding Visual Question Answering With Attention Priors WACV 2023 Video Restoration Framework and Its Meta-Adaptations to Data-Poor Conditions ECCV 2022 Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization ICLR 2022 Learning to Constrain Policy Optimization with Virtual Trust Region NIPS 2022 Expected Improvement for Contextual Bandits NIPS 2022 Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization AISTATS 2022 TRF: Learning Kernels with Tuned Random Features AAAI 2022 Black-Box Few-Shot Knowledge Distillation ECCV 2022 A New Representation of Successor Features for Transfer across Dissimilar Environments ICML 2021 High Dimensional Level Set Estimation with Bayesian Neural Network AAAI 2021 Distributional Reinforcement Learning via Moment Matching AAAI 2021 Bayesian Optimistic Optimisation with Exponentially Decaying Regret ICML 2021 Kernel Functional Optimisation NIPS 2021 Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation IJCAI 2020 Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization AAAI 2020 DeepCoDA: personalized interpretability for compositional health data ICML 2020 Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces NIPS 2020 Accelerated Bayesian Optimisation through Weight-Prior Tuning AISTATS 2020 Bayesian Optimization for Categorical and Category-Specific Continuous Inputs AAAI 2020 Distributionally Robust Bayesian Quadrature Optimization AISTATS 2020 Bayesian Functional Optimisation with Shape Prior AAAI 2019 Bayesian Optimization with Unknown Search Space NIPS 2019 Multi-objective Bayesian optimisation with preferences over objectives NIPS 2019 Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation NIPS 2018 Exploiting Strategy-Space Diversity for Batch Bayesian Optimization AISTATS 2018 High Dimensional Bayesian Optimization using Dropout IJCAI 2017 Regret for Expected Improvement over the Best-Observed Value and Stopping Condition ACML 2017 Regret Bounds for Transfer Learning in Bayesian Optimisation AISTATS 2017 High Dimensional Bayesian Optimization with Elastic Gaussian Process ICML 2017 Process-constrained batch Bayesian optimisation NIPS 2017 A Bayesian Nonparametric Approach for Multi-label Classification ACML 2016 Factorial Multi-Task Learning : A Bayesian Nonparametric Approach ICML 2013