v0.10.2

ExplainableAI v0.10.2

Diff since v0.10.1

Merged pull requests:

• Tested GPU support for Gradient, InputTimesGradient, SmoothGrad, IntegratedGradients (#184) (@adrhill)

v0.10.1

ExplainableAI v0.10.1

Diff since v0.10.0

Merged pull requests:

• Fix bug in NoiseAugmentation constructor, improve docs (#183) (@adrhill)

v0.10.0

ExplainableAI v0.10.0

Diff since v0.9.0

• Fix default noise level for NoiseAugmentation (#179)
• Constant memory input augmentations (#180)

Merged pull requests:

• Bump codecov/codecov-action from 4 to 5 (#178) (@dependabot[bot])
• Fix default noise level for NoiseAugmentation (#179) (@adrhill)
• Constant memory input augmentations (#180) (@adrhill)
• Update DifferentiationInterface dependency (#181) (@adrhill)
• Remove heatmapping docs (#182) (@adrhill)

v0.9.0

ExplainableAI v0.9.0

Diff since v0.8.1

• Support selection of AD backends via DifferentiationInterface.jl. (#167)
• For gradient-based XAI methods, an AD backend must now be manually loaded. To keep using the default Zygote backend, this simply requires adding using Zygote to your code. (#177)
• Gradient, InputTimesGradient and GradCAM analyzers now have an additional backend field and type parameter. (#167)
• Update XAIBase interface to v4. This adds a field to the Explanation return type and removes the add_batch_dim keyword argument. Refer to the XAIBase.jl changelog for more information. (#174)

Merged pull requests:

• Update XAIBase dependency to v4.0.0 (#166) (@adrhill)
• Use DifferentiationInterface for gradient-based analyzers (#167) (@adrhill)
• Update CI workflows (#170) (@adrhill)
• Update CI: Give CompatHelper permission to write PRs (#172) (@adrhill)
• Update CompatHelper v2 (#173) (@adrhill)
• Drop compatibility with pre-LTS versions (#174) (@adrhill)
• Update benchmarks and test them with PkgJogger (#175) (@adrhill)
• Add full example to README (#176) (@adrhill)
• Remove Zygote from dependencies (#177) (@adrhill)

Closed issues:

• Use AbstractDifferentiation.jl (#7)
• Allow selection of AD backends via DifferentiationInterface (#165)
• Update benchmarks (#168)
• Incomplete starter code (#169)
• Update benchmarks and test them with PkgJogger (#171)

v0.8.1

ExplainableAI v0.8.1

Diff since v0.8.0

Merged pull requests:

• Test type stability with JET.jl (#163) (@adrhill)

v0.8.0

ExplainableAI v0.8.0

Diff since v0.7.0

This release removes the automatic reexport of heatmapping functionality.
Users are now required to manually load VisionHeatmaps.jl and/or TextHeatmaps.jl.

This reduces the maintenance burden for new heatmapping features and the amount of dependencies for users who don't require heatmapping functionality.

• Removed reexport of heatmapping functionality by updating XAIBase dependency (#162).
• Added GradCAM analyzer (#155). Try it with VisionHeatmaps.jl's new heatmap_overlay feature.

Merged pull requests:

• Add GradCAM analyzer (#155) (@JeanAnNess)
• Bump codecov/codecov-action from 3 to 4 (#161) (@dependabot[bot])
• Update XAIBase to v3.0.0 and document heatmap_overlay (#162) (@adrhill)

v0.7.0

ExplainableAI v0.7.0

Diff since v0.6.3

This release moves the core interface (Explanation, heatmap, analyze) into a separate package called XAIBase.jl. Developers can make use of the XAIBase.jl interface to quickly implement or prototype new methods without having to write boilerplate code.

As announced with version v0.6.2, this is first release without LRP, which has been moved to a separate package called RelevancePropagation.jl. This separation is enabled by the new common XAIBase.jl interface.

Notable changes

• Move core interface into XAIBase.jl package (#154).
  • Renamed Explanation field neuron_selection to output_selection
  • Added Explanation field heatmap for heatmapping presets
• Move LRP into RelevancePropagation.jl (#157)
• Remove ImageNet preprocessing utilities (#159)
• Partially move documentation into the Julia-XAI ecosystem documentation

Merged pull requests:

• Move core interface into XAIBase.jl package (#154) (@adrhill)
• Bump actions/cache from 3 to 4 (#156) (@dependabot[bot])
• Move LRP into RelevancePropagation.jl (#157) (@adrhill)
• Remove ImageNet preprocessing utilities (#159) (@adrhill)
• Remove unused dependencies and utils (#160) (@adrhill)

Closed issues:

• LRP rule coverage for Flux layers (#9)
• Add visualization method for language models (#79)
• Add XAIBase dependency (#151)
• Move LRP into separate package (#152)
• Remove ImageNet preprocessing code (#153)
• Update README before 1.0 release (#158)

v0.6.3

ExplainableAI v0.6.3

Diff since v0.6.2

Merged pull requests:

• Allow Gradient analyzers on non-Flux models (#150) (@adrhill)

v0.6.2

ExplainableAI v0.6.2

Diff since v0.6.1

Merged pull requests:

• Add Concept Relevance Propagation (#146) (@adrhill)
• Fix EpsilonPlusFlat and EpsilonAlpha2Beta1Flat composites (#147) (@adrhill)
• Document CRP (#148) (@adrhill)
• Transfer repository to Julia-XAI organization (#149) (@adrhill)

v0.6.1

ExplainableAI v0.6.1

Diff since v0.6.0

Merged pull requests:

• Bump actions/checkout from 3 to 4 (#139) (@dependabot[bot])
• Fix neuron selection on GPUs (#140) (@adrhill)
• Make Tullio weak dependency using package extensions (#141) (@adrhill)
• Fix ones_like on GPUs (#142) (@adrhill)
• Improve LRP backward pass (#143) (@adrhill)
• GPU support for gradient analyzers (#144) (@adrhill)
• Document GPU support (#145) (@adrhill)

Closed issues:

• Test for type stability of analyzers (#34)
• Use multithreading in batch gradient computation (#63)