{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:KZ3YWLYZ3BRV3M6NGL3YPS3CNV","short_pith_number":"pith:KZ3YWLYZ","canonical_record":{"source":{"id":"2106.07688","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-14T18:12:10Z","cross_cats_sorted":["nlin.AO"],"title_canon_sha256":"ec1328e5f09861b2d47fe4187f44196b3881023e112083b47b9d5b008fb472aa","abstract_canon_sha256":"9e4d5595db4426f63e992a51165136778651853c9fb1d94ce83f961deee4542e"},"schema_version":"1.0"},"canonical_sha256":"56778b2f19d8635db3cd32f787cb626d7c929b2ba4393f910cc3efa1fcea5b3a","source":{"kind":"arxiv","id":"2106.07688","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.07688","created_at":"2026-07-05T03:16:18Z"},{"alias_kind":"arxiv_version","alias_value":"2106.07688v2","created_at":"2026-07-05T03:16:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.07688","created_at":"2026-07-05T03:16:18Z"},{"alias_kind":"pith_short_12","alias_value":"KZ3YWLYZ3BRV","created_at":"2026-07-05T03:16:18Z"},{"alias_kind":"pith_short_16","alias_value":"KZ3YWLYZ3BRV3M6N","created_at":"2026-07-05T03:16:18Z"},{"alias_kind":"pith_short_8","alias_value":"KZ3YWLYZ","created_at":"2026-07-05T03:16:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:KZ3YWLYZ3BRV3M6NGL3YPS3CNV","target":"record","payload":{"canonical_record":{"source":{"id":"2106.07688","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-14T18:12:10Z","cross_cats_sorted":["nlin.AO"],"title_canon_sha256":"ec1328e5f09861b2d47fe4187f44196b3881023e112083b47b9d5b008fb472aa","abstract_canon_sha256":"9e4d5595db4426f63e992a51165136778651853c9fb1d94ce83f961deee4542e"},"schema_version":"1.0"},"canonical_sha256":"56778b2f19d8635db3cd32f787cb626d7c929b2ba4393f910cc3efa1fcea5b3a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:16:18.698738Z","signature_b64":"0pZqBIWmlxXGwfNqtFzzRZ4Bb7dAYnpXT+ttdieARRYWqYpuYIEg3N+w/AXPjBMJE7gpFjhyUfHIXvj1zU6sCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"56778b2f19d8635db3cd32f787cb626d7c929b2ba4393f910cc3efa1fcea5b3a","last_reissued_at":"2026-07-05T03:16:18.698226Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:16:18.698226Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.07688","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":"2026-07-05T03:16:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R4wD7ydSDufICUN8Hu16PQ9AwVolXAs7GgACkYHzqUFFIf0m9mKpMQwekD3xpnuBopNWON6WyWAzb0CfuLxOBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T23:08:30.662254Z"},"content_sha256":"a9bead9d9a830ab1d3950906f1303ef2a10471a004246a8a6a42e8961b228bd2","schema_version":"1.0","event_id":"sha256:a9bead9d9a830ab1d3950906f1303ef2a10471a004246a8a6a42e8961b228bd2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:KZ3YWLYZ3BRV3M6NGL3YPS3CNV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Next Generation Reservoir Computing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["nlin.AO"],"primary_cat":"cs.LG","authors_text":"Aaron Griffith, Daniel J. Gauthier, Erik Bollt, Wendson A.S. Barbosa","submitted_at":"2021-06-14T18:12:10Z","abstract_excerpt":"Reservoir computing is a best-in-class machine learning algorithm for processing information generated by dynamical systems using observed time-series data. Importantly, it requires very small training data sets, uses linear optimization, and thus requires minimal computing resources. However, the algorithm uses randomly sampled matrices to define the underlying recurrent neural network and has a multitude of metaparameters that must be optimized. Recent results demonstrate the equivalence of reservoir computing to nonlinear vector autoregression, which requires no random matrices, fewer metap"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.07688","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/2106.07688/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":"2026-07-05T03:16:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Wgb6T8Qwp3SV71pxIqoP6tc7viJPE4HlE8bX/B/L10fI7igINwoovSQHradIvQ2TWKT6svJIb7caTJJulIBzDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T23:08:30.664533Z"},"content_sha256":"83833448014fe3b0de5a66cc8b454febb9188ad3d500e23bf4edf067b69916ad","schema_version":"1.0","event_id":"sha256:83833448014fe3b0de5a66cc8b454febb9188ad3d500e23bf4edf067b69916ad"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KZ3YWLYZ3BRV3M6NGL3YPS3CNV/bundle.json","state_url":"https://pith.science/pith/KZ3YWLYZ3BRV3M6NGL3YPS3CNV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KZ3YWLYZ3BRV3M6NGL3YPS3CNV/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":"2026-08-17T23:08:30Z","links":{"resolver":"https://pith.science/pith/KZ3YWLYZ3BRV3M6NGL3YPS3CNV","bundle":"https://pith.science/pith/KZ3YWLYZ3BRV3M6NGL3YPS3CNV/bundle.json","state":"https://pith.science/pith/KZ3YWLYZ3BRV3M6NGL3YPS3CNV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KZ3YWLYZ3BRV3M6NGL3YPS3CNV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:KZ3YWLYZ3BRV3M6NGL3YPS3CNV","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":"9e4d5595db4426f63e992a51165136778651853c9fb1d94ce83f961deee4542e","cross_cats_sorted":["nlin.AO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-14T18:12:10Z","title_canon_sha256":"ec1328e5f09861b2d47fe4187f44196b3881023e112083b47b9d5b008fb472aa"},"schema_version":"1.0","source":{"id":"2106.07688","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.07688","created_at":"2026-07-05T03:16:18Z"},{"alias_kind":"arxiv_version","alias_value":"2106.07688v2","created_at":"2026-07-05T03:16:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.07688","created_at":"2026-07-05T03:16:18Z"},{"alias_kind":"pith_short_12","alias_value":"KZ3YWLYZ3BRV","created_at":"2026-07-05T03:16:18Z"},{"alias_kind":"pith_short_16","alias_value":"KZ3YWLYZ3BRV3M6N","created_at":"2026-07-05T03:16:18Z"},{"alias_kind":"pith_short_8","alias_value":"KZ3YWLYZ","created_at":"2026-07-05T03:16:18Z"}],"graph_snapshots":[{"event_id":"sha256:83833448014fe3b0de5a66cc8b454febb9188ad3d500e23bf4edf067b69916ad","target":"graph","created_at":"2026-07-05T03:16:18Z","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/2106.07688/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reservoir computing is a best-in-class machine learning algorithm for processing information generated by dynamical systems using observed time-series data. Importantly, it requires very small training data sets, uses linear optimization, and thus requires minimal computing resources. However, the algorithm uses randomly sampled matrices to define the underlying recurrent neural network and has a multitude of metaparameters that must be optimized. Recent results demonstrate the equivalence of reservoir computing to nonlinear vector autoregression, which requires no random matrices, fewer metap","authors_text":"Aaron Griffith, Daniel J. Gauthier, Erik Bollt, Wendson A.S. Barbosa","cross_cats":["nlin.AO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-14T18:12:10Z","title":"Next Generation Reservoir Computing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.07688","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:a9bead9d9a830ab1d3950906f1303ef2a10471a004246a8a6a42e8961b228bd2","target":"record","created_at":"2026-07-05T03:16:18Z","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":"9e4d5595db4426f63e992a51165136778651853c9fb1d94ce83f961deee4542e","cross_cats_sorted":["nlin.AO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-14T18:12:10Z","title_canon_sha256":"ec1328e5f09861b2d47fe4187f44196b3881023e112083b47b9d5b008fb472aa"},"schema_version":"1.0","source":{"id":"2106.07688","kind":"arxiv","version":2}},"canonical_sha256":"56778b2f19d8635db3cd32f787cb626d7c929b2ba4393f910cc3efa1fcea5b3a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"56778b2f19d8635db3cd32f787cb626d7c929b2ba4393f910cc3efa1fcea5b3a","first_computed_at":"2026-07-05T03:16:18.698226Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:16:18.698226Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0pZqBIWmlxXGwfNqtFzzRZ4Bb7dAYnpXT+ttdieARRYWqYpuYIEg3N+w/AXPjBMJE7gpFjhyUfHIXvj1zU6sCw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:16:18.698738Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.07688","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a9bead9d9a830ab1d3950906f1303ef2a10471a004246a8a6a42e8961b228bd2","sha256:83833448014fe3b0de5a66cc8b454febb9188ad3d500e23bf4edf067b69916ad"],"state_sha256":"fd9a1d970b9c7ea6ce0ab55d599f87c21723b593973c478dcade2ad139ac2e7f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z8zDns5Ch7RdiZ9fZmdeY4PDfszgqS1sXixBDB6U1bLTHMO/qWe0CRpxOK60txu9I0GfHai1DZzlR6d9u1dHAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T23:08:30.673540Z","bundle_sha256":"eb38571968d9b8b8f1f486b0cd5e3134174c4bbd54738c02e3fe0b61a5dea016"}}