Kenyon Ng - Research

Research Interests

My current research focuses on methodologies in Bayesian statistics and deep learning. In simple terms, I develop AI and machine learning tools that turn data into trustworthy insights.

Tabular foundation models

Prediction on numerical data has long been dominated by traditional machine learning methods (e.g. random forests), until the introduction of TabPFN—a tabular foundation model that enables plug-and-play prediction without task-specific training or tuning. I am interested in making these models more reliable (i.e. better calibrated in their uncertainty) and exploring their practical applications.

Generalised Bayes

Most statistical analyses begin with assumptions about the data, and sometimes those assumptions are simply wrong. When that happens, the conclusions can be misleading. My research explores ways to make inference more robust, using methods such as loss-based inference (blog) and predictive Bayes inference (review).

Publications (methodology)

Ng, K., Fong, E., Frazier, D.T., Knoblauch, J., Wei, S., 2025. TabMGP: Martingale Posterior with TabPFN. under review. arxiv, code

Ng, K., Yu, W., Bondell, H.D., 2025. Expectation-propagation for Bayesian empirical likelihood inference. under review. arxiv, code

Ng, K., van der Heide, C., Hodgkinson, L., Wei, S., 2025. Temperature optimization for Bayesian deep learning. Uncertainty in Artificial Intelligence 2025. arxiv, code

Ng, K., Wei, S., 2025. Pathwise gradient variance reduction with control variates in variational inference. Australian Joint Conference on Artificial Intelligence 2024. arxiv

Ng, K., Turlach, B.A., Murray, K., 2019. A flexible sequential Monte Carlo algorithm for parametric constrained regression. Computational Statistics & Data Analysis. arxiv

Publications (applied)

Ng, K., Diepeveen, D., Farre, I., Reeves, K., Biddulph, B., 2022. Grain yield response to sowing time, how many different response curves and maturity groups are there? Developing maturity type grain yield response curves to sowing time in Western Australia. 20th Agronomy Australia Conference. paper