Sebastian W. Ober

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 22

Top Topics

Gaussian Process

Bayesian Models

Variational Inference

Top Venues

Publications

Alexandra Gessner, Sebastian W. Ober, Owen Vickery, Dino Oglic, Talip Uçar
Active learning for affinity prediction of antibodies. CoRR (2024)
Sebastian W. Ober
Towards Improved Variational Inference for Deep Bayesian Models. CoRR (2024)
Sebastian W. Ober, Artem Artemev, Marcel Wagenländer, Rudolfs Grobins, Mark van der Wilk
Recommendations for Baselines and Benchmarking Approximate Gaussian Processes. CoRR (2024)
Henry B. Moss, Sebastian W. Ober, Victor Picheny
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation. AISTATS (2023)
Victor Picheny, Joel Berkeley, Henry B. Moss, Hrvoje Stojic, Uri Granta, Sebastian W. Ober, Artem Artemev, Khurram Ghani, Alexander Goodall, Andrei Paleyes, Sattar Vakili, Sergio Pascual-Diaz, Stratis Markou, Jixiang Qing, Nasrulloh R. B. S. Loka, Ivo Couckuyt
Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow. CoRR (2023)
Henry B. Moss, Sebastian W. Ober, Victor Picheny
Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation. CoRR (2023)
Sebastian W. Ober, Ben Anson, Edward Milsom, Laurence Aitchison
An improved variational approximate posterior for the deep Wishart process. UAI (2023)
Sebastian W. Ober, Ben Anson, Edward Milsom, Laurence Aitchison
An Improved Variational Approximate Posterior for the Deep Wishart Process. CoRR (2023)
Vincent Fortuin, Adrià Garriga-Alonso, Sebastian W. Ober, Florian Wenzel, Gunnar Rätsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison
Bayesian Neural Network Priors Revisited. ICLR (2022)
Pola Schwöbel, Martin Jørgensen, Sebastian W. Ober, Mark van der Wilk
Last Layer Marginal Likelihood for Invariance Learning. AISTATS (2022)
Henry B. Moss, Sebastian W. Ober, Victor Picheny
Information-theoretic Inducing Point Placement for High-throughput Bayesian Optimisation. CoRR (2022)
Laurence Aitchison, Adam X. Yang, Sebastian W. Ober
Deep Kernel Processes. ICML (2021)
Sebastian W. Ober, Laurence Aitchison
A variational approximate posterior for the deep Wishart process. CoRR (2021)
Pola Elisabeth Schwöbel, Martin Jørgensen, Sebastian W. Ober, Mark van der Wilk
Last Layer Marginal Likelihood for Invariance Learning. CoRR (2021)
Sebastian W. Ober, Laurence Aitchison
A variational approximate posterior for the deep Wishart process. NeurIPS (2021)
Sebastian W. Ober, Carl E. Rasmussen, Mark van der Wilk
The promises and pitfalls of deep kernel learning. UAI (2021)
Sebastian W. Ober, Laurence Aitchison
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes. ICML (2021)
Sebastian W. Ober, Carl E. Rasmussen, Mark van der Wilk
The Promises and Pitfalls of Deep Kernel Learning. CoRR (2021)
David R. Burt, Sebastian W. Ober, Adrià Garriga-Alonso, Mark van der Wilk
Understanding Variational Inference in Function-Space. CoRR (2020)
Sebastian W. Ober, Laurence Aitchison
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes. CoRR (2020)
Laurence Aitchison, Adam X. Yang, Sebastian W. Ober
Deep kernel processes. CoRR (2020)
Sebastian W. Ober, Carl Edward Rasmussen
Benchmarking the Neural Linear Model for Regression. CoRR (2019)