{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:ZUBI5Q6QK4M6FQVFX3W25CRMTV","short_pith_number":"pith:ZUBI5Q6Q","canonical_record":{"source":{"id":"2304.02119","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2023-04-04T20:57:34Z","cross_cats_sorted":["cs.LG","cs.SY"],"title_canon_sha256":"87ed9360bbb382c093e743dc868136f648bb8170aa3c005f1bf49850fca78f21","abstract_canon_sha256":"bd442bc7f65c883c457a8cfedf6d2b3f554bacf1f530096487c2694e4838151c"},"schema_version":"1.0"},"canonical_sha256":"cd028ec3d05719e2c2a5beedae8a2c9d77df0074691c2fc235846972516d949b","source":{"kind":"arxiv","id":"2304.02119","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.02119","created_at":"2026-07-05T05:58:53Z"},{"alias_kind":"arxiv_version","alias_value":"2304.02119v2","created_at":"2026-07-05T05:58:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.02119","created_at":"2026-07-05T05:58:53Z"},{"alias_kind":"pith_short_12","alias_value":"ZUBI5Q6QK4M6","created_at":"2026-07-05T05:58:53Z"},{"alias_kind":"pith_short_16","alias_value":"ZUBI5Q6QK4M6FQVF","created_at":"2026-07-05T05:58:53Z"},{"alias_kind":"pith_short_8","alias_value":"ZUBI5Q6Q","created_at":"2026-07-05T05:58:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:ZUBI5Q6QK4M6FQVFX3W25CRMTV","target":"record","payload":{"canonical_record":{"source":{"id":"2304.02119","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2023-04-04T20:57:34Z","cross_cats_sorted":["cs.LG","cs.SY"],"title_canon_sha256":"87ed9360bbb382c093e743dc868136f648bb8170aa3c005f1bf49850fca78f21","abstract_canon_sha256":"bd442bc7f65c883c457a8cfedf6d2b3f554bacf1f530096487c2694e4838151c"},"schema_version":"1.0"},"canonical_sha256":"cd028ec3d05719e2c2a5beedae8a2c9d77df0074691c2fc235846972516d949b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:58:53.996843Z","signature_b64":"wLwpTYgkGZF9dGy7sgEAinhl+tibajMhfO4pFjJRaXc6eyIekwTmLVyNVZPLlRu4b/whazM6vNanTEFGUC0vCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cd028ec3d05719e2c2a5beedae8a2c9d77df0074691c2fc235846972516d949b","last_reissued_at":"2026-07-05T05:58:53.996500Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:58:53.996500Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.02119","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:58:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kXz79F/NdzhVBO4nRptl7LVAf3St03h/XeDnIcjSnfTl6pmM6kWGteho30w3CC3HAIn61bcxjBVF38KnhZs9AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T15:02:08.312703Z"},"content_sha256":"30401dd79c262696052ab00fbc8219be282573add48b74f891e2e69ba412f158","schema_version":"1.0","event_id":"sha256:30401dd79c262696052ab00fbc8219be282573add48b74f891e2e69ba412f158"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:ZUBI5Q6QK4M6FQVFX3W25CRMTV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SY"],"primary_cat":"eess.SY","authors_text":"Gerben I. Beintema, Maarten Schoukens, Rishi Ramkannan, Roland T\\'oth","submitted_at":"2023-04-04T20:57:34Z","abstract_excerpt":"The SUBNET neural network architecture has been developed to identify nonlinear state-space models from input-output data. To achieve this, it combines the rolled-out nonlinear state-space equations and a state encoder function, both parameterised as neural networks The encoder function is introduced to reconstruct the current state from past input-output data. Hence, it enables the forward simulation of the rolled-out state-space model. While this approach has shown to provide high-accuracy and consistent model estimation, its convergence can be significantly improved by efficient initializat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.02119","kind":"arxiv","version":2},"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/2304.02119/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:58:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dltSXtr4R1wKkReBXcsD6nYZiVJCsThYhpoBwyU6Z0hMljYN3P+7KSFF1d2sP9ExQZ0bpenVMhqf6knH1L8iAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T15:02:08.313437Z"},"content_sha256":"a6d3858a62d732adb8a999fa38849a32821553eb7aaa3fbe75b2c1f84f59c45f","schema_version":"1.0","event_id":"sha256:a6d3858a62d732adb8a999fa38849a32821553eb7aaa3fbe75b2c1f84f59c45f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZUBI5Q6QK4M6FQVFX3W25CRMTV/bundle.json","state_url":"https://pith.science/pith/ZUBI5Q6QK4M6FQVFX3W25CRMTV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZUBI5Q6QK4M6FQVFX3W25CRMTV/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-21T15:02:08Z","links":{"resolver":"https://pith.science/pith/ZUBI5Q6QK4M6FQVFX3W25CRMTV","bundle":"https://pith.science/pith/ZUBI5Q6QK4M6FQVFX3W25CRMTV/bundle.json","state":"https://pith.science/pith/ZUBI5Q6QK4M6FQVFX3W25CRMTV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZUBI5Q6QK4M6FQVFX3W25CRMTV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:ZUBI5Q6QK4M6FQVFX3W25CRMTV","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"bd442bc7f65c883c457a8cfedf6d2b3f554bacf1f530096487c2694e4838151c","cross_cats_sorted":["cs.LG","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2023-04-04T20:57:34Z","title_canon_sha256":"87ed9360bbb382c093e743dc868136f648bb8170aa3c005f1bf49850fca78f21"},"schema_version":"1.0","source":{"id":"2304.02119","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.02119","created_at":"2026-07-05T05:58:53Z"},{"alias_kind":"arxiv_version","alias_value":"2304.02119v2","created_at":"2026-07-05T05:58:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.02119","created_at":"2026-07-05T05:58:53Z"},{"alias_kind":"pith_short_12","alias_value":"ZUBI5Q6QK4M6","created_at":"2026-07-05T05:58:53Z"},{"alias_kind":"pith_short_16","alias_value":"ZUBI5Q6QK4M6FQVF","created_at":"2026-07-05T05:58:53Z"},{"alias_kind":"pith_short_8","alias_value":"ZUBI5Q6Q","created_at":"2026-07-05T05:58:53Z"}],"graph_snapshots":[{"event_id":"sha256:a6d3858a62d732adb8a999fa38849a32821553eb7aaa3fbe75b2c1f84f59c45f","target":"graph","created_at":"2026-07-05T05:58:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2304.02119/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The SUBNET neural network architecture has been developed to identify nonlinear state-space models from input-output data. To achieve this, it combines the rolled-out nonlinear state-space equations and a state encoder function, both parameterised as neural networks The encoder function is introduced to reconstruct the current state from past input-output data. Hence, it enables the forward simulation of the rolled-out state-space model. While this approach has shown to provide high-accuracy and consistent model estimation, its convergence can be significantly improved by efficient initializat","authors_text":"Gerben I. Beintema, Maarten Schoukens, Rishi Ramkannan, Roland T\\'oth","cross_cats":["cs.LG","cs.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2023-04-04T20:57:34Z","title":"Initialization Approach for Nonlinear State-Space Identification via the Subspace Encoder Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.02119","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:30401dd79c262696052ab00fbc8219be282573add48b74f891e2e69ba412f158","target":"record","created_at":"2026-07-05T05:58:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"bd442bc7f65c883c457a8cfedf6d2b3f554bacf1f530096487c2694e4838151c","cross_cats_sorted":["cs.LG","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2023-04-04T20:57:34Z","title_canon_sha256":"87ed9360bbb382c093e743dc868136f648bb8170aa3c005f1bf49850fca78f21"},"schema_version":"1.0","source":{"id":"2304.02119","kind":"arxiv","version":2}},"canonical_sha256":"cd028ec3d05719e2c2a5beedae8a2c9d77df0074691c2fc235846972516d949b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cd028ec3d05719e2c2a5beedae8a2c9d77df0074691c2fc235846972516d949b","first_computed_at":"2026-07-05T05:58:53.996500Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:58:53.996500Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wLwpTYgkGZF9dGy7sgEAinhl+tibajMhfO4pFjJRaXc6eyIekwTmLVyNVZPLlRu4b/whazM6vNanTEFGUC0vCg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:58:53.996843Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.02119","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:30401dd79c262696052ab00fbc8219be282573add48b74f891e2e69ba412f158","sha256:a6d3858a62d732adb8a999fa38849a32821553eb7aaa3fbe75b2c1f84f59c45f"],"state_sha256":"4ced14481bda57348fed4ce0f6cbbf13073d31594facb5fd6e194af0f9eea838"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5gf7fbFoMRGspJCQPCCex/R26iTS4xEXN/4yKsM+phDp0o3NJNN8/QzW3BcI3ASm0WyGX4EJuiEqzOAZUY3mCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T15:02:08.321849Z","bundle_sha256":"2d74aeeffad673e9b7080f298dc71d2d3672ea412bb772614f4b6b3cbd621908"}}