{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:7OY4PN7CNZQS3AF5YAL5QIWZ7A","short_pith_number":"pith:7OY4PN7C","schema_version":"1.0","canonical_sha256":"fbb1c7b7e26e612d80bdc017d822d9f83ca3c24a98c531e22fb44c4cd954b277","source":{"kind":"arxiv","id":"1605.05628","version":1},"attestation_state":"computed","paper":{"title":"Detecting Novel Processes with CANDIES -- An Holistic Novelty Detection Technique based on Probabilistic Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Bernhard Sick, Christian Gruhl","submitted_at":"2016-05-18T15:47:59Z","abstract_excerpt":"In this article, we propose CANDIES (Combined Approach for Novelty Detection in Intelligent Embedded Systems), a new approach to novelty detection in technical systems. We assume that in a technical system several processes interact. If we observe these processes with sensors, we are able to model the observations (samples) with a probabilistic model, where, in an ideal case, the components of the parametric mixture density model we use, correspond to the processes in the real world. Eventually, at run-time, novel processes emerge in the technical systems such as in the case of an unpredictabl"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1605.05628","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-05-18T15:47:59Z","cross_cats_sorted":[],"title_canon_sha256":"53b16fc864cd4c459653f332afb28cfcc90a09db21f9d0ac3513e4fd84cc38db","abstract_canon_sha256":"cd5b456db1652f956aef8e3c2217e23dfa637d72f8524702c76e99323e0780ec"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:14:34.388654Z","signature_b64":"vDAsDXat4wjvqsLeGtxrMrtpPTfRaikn0WwCBaBf78uJ7TrNBCNmlsVUtp5ATMeDK1mr1UWOeaqVcQjf2cFoCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fbb1c7b7e26e612d80bdc017d822d9f83ca3c24a98c531e22fb44c4cd954b277","last_reissued_at":"2026-05-18T01:14:34.387923Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:14:34.387923Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Detecting Novel Processes with CANDIES -- An Holistic Novelty Detection Technique based on Probabilistic Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Bernhard Sick, Christian Gruhl","submitted_at":"2016-05-18T15:47:59Z","abstract_excerpt":"In this article, we propose CANDIES (Combined Approach for Novelty Detection in Intelligent Embedded Systems), a new approach to novelty detection in technical systems. We assume that in a technical system several processes interact. If we observe these processes with sensors, we are able to model the observations (samples) with a probabilistic model, where, in an ideal case, the components of the parametric mixture density model we use, correspond to the processes in the real world. Eventually, at run-time, novel processes emerge in the technical systems such as in the case of an unpredictabl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.05628","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1605.05628","created_at":"2026-05-18T01:14:34.388030+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.05628v1","created_at":"2026-05-18T01:14:34.388030+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.05628","created_at":"2026-05-18T01:14:34.388030+00:00"},{"alias_kind":"pith_short_12","alias_value":"7OY4PN7CNZQS","created_at":"2026-05-18T12:30:04.600751+00:00"},{"alias_kind":"pith_short_16","alias_value":"7OY4PN7CNZQS3AF5","created_at":"2026-05-18T12:30:04.600751+00:00"},{"alias_kind":"pith_short_8","alias_value":"7OY4PN7C","created_at":"2026-05-18T12:30:04.600751+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7OY4PN7CNZQS3AF5YAL5QIWZ7A","json":"https://pith.science/pith/7OY4PN7CNZQS3AF5YAL5QIWZ7A.json","graph_json":"https://pith.science/api/pith-number/7OY4PN7CNZQS3AF5YAL5QIWZ7A/graph.json","events_json":"https://pith.science/api/pith-number/7OY4PN7CNZQS3AF5YAL5QIWZ7A/events.json","paper":"https://pith.science/paper/7OY4PN7C"},"agent_actions":{"view_html":"https://pith.science/pith/7OY4PN7CNZQS3AF5YAL5QIWZ7A","download_json":"https://pith.science/pith/7OY4PN7CNZQS3AF5YAL5QIWZ7A.json","view_paper":"https://pith.science/paper/7OY4PN7C","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.05628&json=true","fetch_graph":"https://pith.science/api/pith-number/7OY4PN7CNZQS3AF5YAL5QIWZ7A/graph.json","fetch_events":"https://pith.science/api/pith-number/7OY4PN7CNZQS3AF5YAL5QIWZ7A/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7OY4PN7CNZQS3AF5YAL5QIWZ7A/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7OY4PN7CNZQS3AF5YAL5QIWZ7A/action/storage_attestation","attest_author":"https://pith.science/pith/7OY4PN7CNZQS3AF5YAL5QIWZ7A/action/author_attestation","sign_citation":"https://pith.science/pith/7OY4PN7CNZQS3AF5YAL5QIWZ7A/action/citation_signature","submit_replication":"https://pith.science/pith/7OY4PN7CNZQS3AF5YAL5QIWZ7A/action/replication_record"}},"created_at":"2026-05-18T01:14:34.388030+00:00","updated_at":"2026-05-18T01:14:34.388030+00:00"}