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Robust Gaussian Processes via Relevance Pursuit #2608

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Robust Gaussian Processes via Relevance Pursuit #2608

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7 changes: 6 additions & 1 deletion botorch/models/gpytorch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -402,6 +402,8 @@ def _apply_noise(
mvn = self.likelihood(mvn, X)
return mvn

# pyre-ignore[14]: Inconsistent override. Could not find parameter
# `Keywords(typing.Any)` in overriding signature.
def posterior(
self,
X: Tensor,
Expand Down Expand Up @@ -470,6 +472,7 @@ def posterior(
return posterior_transform(posterior)
return posterior

# pyre-ignore[14]: Inconsistent override. Could not find parameter `noise`.
def condition_on_observations(
self, X: Tensor, Y: Tensor, **kwargs: Any
) -> BatchedMultiOutputGPyTorchModel:
Expand Down Expand Up @@ -632,7 +635,7 @@ def batch_shape(self) -> torch.Size:
raise NotImplementedError(msg + " that are not broadcastble.")
return next(iter(batch_shapes))

# pyre-fixme[15]: Inconsistent override in return types
# pyre-fixme[14]: Inconsistent override in return types
def posterior(
self,
X: Tensor,
Expand Down Expand Up @@ -838,6 +841,8 @@ def _apply_noise(
)
return self.likelihood(mvn, X)

# pyre-ignore[14]: Inconsistent override. Could not find parameter
# `Keywords(typing.Any)` in overriding signature.
def posterior(
self,
X: Tensor,
Expand Down
480 changes: 480 additions & 0 deletions botorch/models/likelihoods/sparse_outlier_noise.py
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