24 citations · 168 across the 34 of their papers we have counts for
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stat.ML2023★ 1 cited
An Improved Variational Approximate Posterior for the Deep Wishart Process
Sebastian Ober, Ben Anson, Edward Milsom +1
Deep kernel processes are a recently introduced class of deep Bayesian models that have the flexibility of neural networks, but work entirely with Gram matrices. They operate by al…
stat.ML2023★ 1 cited
Decision trees compensate for model misspecification
Hugh Panton, Gavin Leech, Laurence Aitchison
The best-performing models in ML are not interpretable. If we can explain why they outperform, we may be able to replicate these mechanisms and obtain both interpretability and per…