{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:4ZARVCHNZS3CZ2WPGL7QGKY2AG","short_pith_number":"pith:4ZARVCHN","schema_version":"1.0","canonical_sha256":"e6411a88edccb62ceacf32ff032b1a0197cd524f04e5a0ab61a2a40f6a911993","source":{"kind":"arxiv","id":"2206.09992","version":1},"attestation_state":"computed","paper":{"title":"Hyperparameter Importance of Quantum Neural Networks Across Small Datasets","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"quant-ph","authors_text":"Charles Moussa, Jan N. van Rijn, Thomas B\\\"ack, Vedran Dunjko","submitted_at":"2022-06-20T20:26:20Z","abstract_excerpt":"As restricted quantum computers are slowly becoming a reality, the search for meaningful first applications intensifies. In this domain, one of the more investigated approaches is the use of a special type of quantum circuit - a so-called quantum neural network -- to serve as a basis for a machine learning model. Roughly speaking, as the name suggests, a quantum neural network can play a similar role to a neural network. However, specifically for applications in machine learning contexts, very little is known about suitable circuit architectures, or model hyperparameters one should use to achi"},"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":"2206.09992","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2022-06-20T20:26:20Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7c36c34f02a4d8f802e0dde1ac38502f4eebea1e19646f021d8cec238eac6ebc","abstract_canon_sha256":"8549763a569606c0ac317ef6fdf4a0641126873865edba9d04a29054e5309ac9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:13:34.985999Z","signature_b64":"DDIdC8nKNBYxdVNWqQQIwDck74fC8hb01jFwsZrjaSZKwj57jPw+sm43x48sRhCuEy+VABTQQT02CL/yq2m3Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e6411a88edccb62ceacf32ff032b1a0197cd524f04e5a0ab61a2a40f6a911993","last_reissued_at":"2026-07-05T05:13:34.985451Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:13:34.985451Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Hyperparameter Importance of Quantum Neural Networks Across Small Datasets","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"quant-ph","authors_text":"Charles Moussa, Jan N. van Rijn, Thomas B\\\"ack, Vedran Dunjko","submitted_at":"2022-06-20T20:26:20Z","abstract_excerpt":"As restricted quantum computers are slowly becoming a reality, the search for meaningful first applications intensifies. In this domain, one of the more investigated approaches is the use of a special type of quantum circuit - a so-called quantum neural network -- to serve as a basis for a machine learning model. Roughly speaking, as the name suggests, a quantum neural network can play a similar role to a neural network. However, specifically for applications in machine learning contexts, very little is known about suitable circuit architectures, or model hyperparameters one should use to achi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.09992","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2206.09992/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2206.09992","created_at":"2026-07-05T05:13:34.985517+00:00"},{"alias_kind":"arxiv_version","alias_value":"2206.09992v1","created_at":"2026-07-05T05:13:34.985517+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.09992","created_at":"2026-07-05T05:13:34.985517+00:00"},{"alias_kind":"pith_short_12","alias_value":"4ZARVCHNZS3C","created_at":"2026-07-05T05:13:34.985517+00:00"},{"alias_kind":"pith_short_16","alias_value":"4ZARVCHNZS3CZ2WP","created_at":"2026-07-05T05:13:34.985517+00:00"},{"alias_kind":"pith_short_8","alias_value":"4ZARVCHN","created_at":"2026-07-05T05:13:34.985517+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/4ZARVCHNZS3CZ2WPGL7QGKY2AG","json":"https://pith.science/pith/4ZARVCHNZS3CZ2WPGL7QGKY2AG.json","graph_json":"https://pith.science/api/pith-number/4ZARVCHNZS3CZ2WPGL7QGKY2AG/graph.json","events_json":"https://pith.science/api/pith-number/4ZARVCHNZS3CZ2WPGL7QGKY2AG/events.json","paper":"https://pith.science/paper/4ZARVCHN"},"agent_actions":{"view_html":"https://pith.science/pith/4ZARVCHNZS3CZ2WPGL7QGKY2AG","download_json":"https://pith.science/pith/4ZARVCHNZS3CZ2WPGL7QGKY2AG.json","view_paper":"https://pith.science/paper/4ZARVCHN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2206.09992&json=true","fetch_graph":"https://pith.science/api/pith-number/4ZARVCHNZS3CZ2WPGL7QGKY2AG/graph.json","fetch_events":"https://pith.science/api/pith-number/4ZARVCHNZS3CZ2WPGL7QGKY2AG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4ZARVCHNZS3CZ2WPGL7QGKY2AG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4ZARVCHNZS3CZ2WPGL7QGKY2AG/action/storage_attestation","attest_author":"https://pith.science/pith/4ZARVCHNZS3CZ2WPGL7QGKY2AG/action/author_attestation","sign_citation":"https://pith.science/pith/4ZARVCHNZS3CZ2WPGL7QGKY2AG/action/citation_signature","submit_replication":"https://pith.science/pith/4ZARVCHNZS3CZ2WPGL7QGKY2AG/action/replication_record"}},"created_at":"2026-07-05T05:13:34.985517+00:00","updated_at":"2026-07-05T05:13:34.985517+00:00"}