| 2025 | ICML | Return of the Latent Space COWBOYS: Re-thinking the use of VAEs for Bayesian Optimisation of Structured Spaces. | Henry B. Moss, Sebastian W. Ober, Tom Diethe |
| 2023 | AISTATS | Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation. | Henry B. Moss, Sebastian W. Ober, Victor Picheny |
| 2023 | UAI | An improved variational approximate posterior for the deep Wishart process. | Sebastian W. Ober, Ben Anson, Edward Milsom, Laurence Aitchison |
| 2022 | AISTATS | Last Layer Marginal Likelihood for Invariance Learning. | Pola Schwbel, Martin Jrgensen, Sebastian W. Ober, Mark van der Wilk |
| 2022 | ICLR | Bayesian Neural Network Priors Revisited. | Vincent Fortuin, Adri Garriga-Alonso, Sebastian W. Ober, Florian Wenzel, Gunnar Rtsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison |
| 2021 | ICML | Deep Kernel Processes. | Laurence Aitchison, Adam X. Yang, Sebastian W. Ober |
| 2021 | ICML | Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes. | Sebastian W. Ober, Laurence Aitchison |
| 2021 | UAI | The promises and pitfalls of deep kernel learning. | Sebastian W. Ober, Carl E. Rasmussen, Mark van der Wilk |
| 2017 | BSN | Modeling and detecting student attention and interest level using wearable computers. | Ziwei Zhu, Sebastian W. Ober, Roozbeh Jafari |