v0.6.0

ExplainableAI v0.6.0

Diff since v0.5.7

Closed issues:

• Add LRP support for Parallel layer (#10)
• Document use of LoopVectorization.jl and CUDA.jl (#64)
• Add LRP support for nested Chains (#90)
• Add generalized Gamma rule (#91)
• Rename composite primitives (#120)
• Add composite primitive to assign rule at specific position in model (#121)
• Support BatchNorm layers in LRP (#122)
• Refactor results struct (#123)
• Add Aqua.jl tests (#124)
• Update canonizer to support nested Flux Chains (#132)
• Update documentation for v0.6.0 release (#133)

Merged pull requests:

• Add GeneralizedGammaRule (#109) (@adrhill)
• Simplify LRP analyzer and clean-up rule default parameters (#110) (@adrhill)
• Simplify LRP model checks (#112) (@adrhill)
• Update dependencies (#116) (@adrhill)
• Bump actions/cache from 1 to 3 (#117) (@dependabot[bot])
• Bump actions/checkout from 2 to 3 (#118) (@dependabot[bot])
• Support nested Flux Chains in LRP (#119) (@adrhill)
• Add Aqua.jl tests (#125) (@adrhill)
• Refactor Explanation struct (#126) (@adrhill)
• Faster tests and benchmarks (#127) (@adrhill)
• Set LRP output relevance to one (#128) (@adrhill)
• Enable BatchNorm layers in LRP (#129) (@adrhill)
• Rename composite primitives (#130) (@adrhill)
• Support nested indexing in composite primitive LayerMap (#131) (@adrhill)
• Add PassRule on normalization layers to composite presets, improve show (#134) (@adrhill)
• Support Parallel layers in LRP (#135) (@adrhill)
• Rename Explanation field attribution to val (#136) (@adrhill)
• Update documentation for v0.6.0 (#137) (@adrhill)
• Support canonization of Parallel layers (#138) (@adrhill)