13 citations · 26 across the 13 of their papers we have counts for
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cs.LG2023
Accelerating Non-Conjugate Gaussian Processes By Trading Off Computation For Uncertainty
Lukas Tatzel, Jonathan Wenger, Frank Schneider +1
Non-conjugate Gaussian processes (NCGPs) define a flexible probabilistic framework to model categorical, ordinal and continuous data, and are widely used in practice. However, exac…
cs.LG2023★ 1 cited
Large-Scale Gaussian Processes via Alternating Projection
Kaiwen Wu, Jonathan Wenger, Haydn Jones +2
Training and inference in Gaussian processes (GPs) require solving linear systems with kernel matrices. To address the prohibitive time complexity, r…
cs.LG2023★ 1 cited
On the Disconnect Between Theory and Practice of Neural Networks: Limits of the NTK Perspective
Jonathan Wenger, Felix Dangel, Agustinus Kristiadi
The neural tangent kernel (NTK) has garnered significant attention as a theoretical framework for describing the behavior of large-scale neural networks. Kernel methods are theoret…