{
  "id": "2103.13533",
  "version": "v1",
  "published": "2021-03-25T00:09:09.000Z",
  "updated": "2021-03-25T00:09:09.000Z",
  "title": "Symmetry-Preserving Paths in Integrated Gradients",
  "authors": [
    "Miguel Lerma",
    "Mirtha Lucas"
  ],
  "comment": "7 pages, 1 figure",
  "categories": [
    "cs.LG",
    "cs.AI"
  ],
  "abstract": "We provide rigorous proofs that the Integrated Gradients (IG) attribution method for deep networks satisfies completeness and symmetry-preserving properties. We also study the uniqueness of IG as a path method preserving symmetry.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2021-03-25T00:09:09.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "68T07",
      "I.2.m"
    ],
    "keywords": [
      "integrated gradients",
      "symmetry-preserving paths",
      "deep networks satisfies completeness",
      "path method preserving symmetry",
      "attribution method"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 7,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}