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PyPI · #4690 most downloaded on PyPI
A linear operator implementation, primarily designed for finite-dimensional positive definite operators (i.e. kernel matrices).
Last release 7 months ago
27 Feb 2026
Release timing varies
gaps range from 3 weeks to 13 months
Nearly every release is documented
notes for 10 of 11 stable releases
Nothing withdrawn
no release was ever pulled
4 years old
11 releases · first in 2022
Update deprecated sparse tensor construction by @Balandat in https://github.com/cornellius-gp/linear_operator/pull/110
base_linear_op to a dense linear operator in BlockDiagLinearOperator by @kayween in https://github.com/cornellius-gp/linear_operator/pull/119Full Changelog: https://github.com/cornellius-gp/linear_operator/compare/v0.6...v0.6.1
One column per quarter.
Corrected configuration of exclude statements in pre-commit configuration by @JonathanWenger in https://github.com/cornellius-gp/linear_operator/pull/
LinearOperator now requires
exclude statements in pre-commit configuration by @JonathanWenger in https://github.com/cornellius-gp/linear_operator/pull/104Full Changelog: https://github.com/cornellius-gp/linear_operator/compare/v0.5.3...v0.6
Fix issue with negative indexing in CatLinearOperator by @Balandat in https://github.com/cornellius-gp/linear_operator/pull/80
CatLinearOperator by @Balandat in https://github.com/cornellius-gp/linear_operator/pull/80Full Changelog: https://github.com/cornellius-gp/linear_operator/compare/v0.5.2...v0.5.3
Fix type error when converting interpolated_linear_operator to double precision by @CY-Zhang in https://github.com/cornellius-gp/linear_operator/pull/
Full Changelog: https://github.com/cornellius-gp/linear_operator/compare/v0.5.1...v0.5.2
Fix type of KroneckerProductLinearOperator.linear_ops (in some cases) by @Balandat in https://github.com/cornellius-gp/linear_operator/pull/66
Full Changelog: https://github.com/cornellius-gp/linear_operator/compare/v0.5.0...v0.5.1
Clean up deprecation warnings by @saitcakmak in https://github.com/cornellius-gp/linear_operator/pull/63
DiagLinearOperator if its _diag is a scalar tensor by @Balandat in https://github.com/cornellius-gp/linear_operator/pull/61Full Changelog: https://github.com/cornellius-gp/linear_operator/compare/v0.4.0...v0.5.0
Use raw strings to avoid "DeprecationWarning: invalid escape sequence" by @saitcakmak in https://github.com/cornellius-gp/linear_operator/pull/52
.to() to operate on tensors by @Balandat in https://github.com/cornellius-gp/linear_operator/pull/45*_value. by @Balandat in https://github.com/cornellius-gp/linear_operator/pull/47Full Changelog: https://github.com/cornellius-gp/linear_operator/compare/V0.3.0...v0.4.0
Nothing published for this version
Add basic example notebook by @Balandat in https://github.com/cornellius-gp/linear_operator/pull/17
BlockDiagLinearOperator by DiagLinearOperator by @SebastianAment in https://github.com/cornellius-gp/linear_operator/pull/14add, BlockDiagLinearOperator's matmul, and documentation by @SebastianAment in https://github.com/cornellius-gp/linear_operator/pull/10deepcopy in add because of downstream failure in BoTorch by @SebastianAment in https://github.com/cornellius-gp/linear_operator/pull/12ConstantDiagLinearOperator._mul_constant and ConstantMulLinearOperator._getitem. by @j-wilson in https://github.com/cornellius-gp/linear_operator/pull/37Full Changelog: https://github.com/cornellius-gp/linear_operator/compare/v0.1.1...v0.2.0
Full Changelog: https://github.com/cornellius-gp/linear_operator/compare/v0.1.0...v0.1.1
Full Changelog: https://github.com/cornellius-gp/linear_operator/compare/v0.1.0...v0.1.1
This repo is in charge of what was previously known as LazyTensor in GPyTorch. It is currently a package that is predominantly used within GPyTorch, a
This repo is in charge of what was previously known as LazyTensor in GPyTorch. It is currently a package that is predominantly used within GPyTorch, and assumes that the LinearOperators will be PSD kernel matrices. In the future, the goal is to make this a more generic implementation of LinearOperators that can be used in any number of applications.
For now, this implementation is very similar to what is currently in GPyTorch (v1.8.1). The only major difference is that *LazyTensor has been renamed to *LinearOperator.
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