SGPR 的 GPflow 多输出支持
GPflow multi-output support for SGPR
GPflow 似乎只支持 SVGP 的多输出。是否可以将这种多输出支持用于其他模型（例如 SGPR）？例如：
kernel = mk.SharedIndependentMok(gpf.kernels.RBF(D), P)
feature = features.InducingPoints(X[:M,...].copy())
m = gpf.models.SGPR(X, Y, kernel, feature)
这是一个确定的问题（https://github.com/GPflow/GPflow/issues/1209), that currently has comparatively low priority for the GPflow core developers - but we'd be very happy for you to join us and contribute features! There is now a public GPflow slack 以便于讨论。
GPflow 似乎只支持 SVGP 的多输出。是否可以将这种多输出支持用于其他模型（例如 SGPR）？例如：
kernel = mk.SharedIndependentMok(gpf.kernels.RBF(D), P)
feature = features.InducingPoints(X[:M,...].copy())
m = gpf.models.SGPR(X, Y, kernel, feature)
这是一个确定的问题（https://github.com/GPflow/GPflow/issues/1209), that currently has comparatively low priority for the GPflow core developers - but we'd be very happy for you to join us and contribute features! There is now a public GPflow slack 以便于讨论。