Invited Presentations
- Mar-2025
- Credal Two-Sample Tests：How to Test Hypothesis Under Dataset Uncertainty
- RainML Research Lab, Department of Statistics, University of Oxford
- Mar-2025
- Credal Two-Sample Tests：How to Test Hypothesis Under Dataset Uncertainty
- Manchester Centre for AI Fundamentals, University of Manchester
- Feb-2025
- Towards Credal Generalisation： How to Learn and Test Hypothesis under Dataset Uncertainty?
- Amazon Web Service, Berlin
- Oct-2024
- Credal Two-Sample Tests of Epistemic Ignorance
- Department of Statistical Science, University College London
- Oct-2024
- Credal Two-Sample Tests of Epistemic Ignorance
- Gatsby Computational Neuroscience Unit, University College London
- Aug-2024
- Introduction to the role of Uncertainty in Machine Learning
- Kernels and Information Processing Systems group, University of Adelaide
- Jul-2024
- Introduction to the role of Uncertainty in Machine Learning
- College of Computing and Data Science, Nanyang Technological University
- Mar-2024
- Stochastic Shapley Values for Gaussian Processes and application to Explainable Bayesian Optimisation
- Institute for Informatics, LMU
- Dec-2023
- Stochastic Shapley Values for Gaussian Processes
- Australian Data Science Network
- Nov-2023
- Collaborative and Explainable Bayesian Optimisation
- Data 61 Melbourne
- Nov-2023
- Stochastic Shapley Values for Gaussian Processes
- School of Computing, Australian National University
- Nov-2023
- Collaborative and Explainable Bayesian Optimisation
- School of Computing and Information Systems, The University of Melbourne
- Nov-2023
- Stochastic Shapley Values for Gaussian Processes
- Australian Institute for Machine Learning (AIML)
- Sep-2023
- Stochastic Shapley Values for Gaussian Processes
- Oxford Man Institute, University of Oxford
- Sep-2023
- Stochastic Shapley Values for Gaussian Processes
- ETH AI Center
- Sep-2023
- Stochastic Shapley Values for Gaussian Processes
- Department of Management, Technology, and Economics (D-MTEC) at ETH Zürich
- Feb-2023
- Introduction to Explainable ML
- Oxford Strategy Group Digital
- Feb-2023
- Explaining kernel methods and preference models with RKHS-SHAP
- CISPA Helmholtz Center for Information Security
- Sep-2022
- Explainability for kernel methods
- ELISE Theory Workshop on ML fundamentals at Eurecom
- Sep-2022
- Spectral ranking with Covariates
- ECML-PKDD
- Jun-2022
- Deconditional Gaussian processes
- S-DCE Alan Turing Institute seminar
- Apr-2022
- Explaining kernel methods with RKHS-SHAP
- UCL Gatsby Unit
- Feb-2022
- Shapley values for model explanations
- Imperial & Oxford STATML seminar
- Jun-2021
- Uncertainty quantification for causal data fusion
- Warwick ML group