{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:2M3DKFUUPIZSLDJMF4HSPENJLH","short_pith_number":"pith:2M3DKFUU","canonical_record":{"source":{"id":"1811.07490","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-11-19T04:07:49Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6729f94c019cdfb6cadc192d08a945321bf8e64bdd5baf544463e99a49541c12","abstract_canon_sha256":"9936a3c04a31d087a5d8f0e577ced468f2247f566ebd5a6fbfa8fd7f38f875fa"},"schema_version":"1.0"},"canonical_sha256":"d3363516947a33258d2c2f0f2791a959f9e0d385025d5799e66f8ed2214efaa8","source":{"kind":"arxiv","id":"1811.07490","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.07490","created_at":"2026-05-17T23:48:06Z"},{"alias_kind":"arxiv_version","alias_value":"1811.07490v3","created_at":"2026-05-17T23:48:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.07490","created_at":"2026-05-17T23:48:06Z"},{"alias_kind":"pith_short_12","alias_value":"2M3DKFUUPIZS","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"2M3DKFUUPIZSLDJM","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"2M3DKFUU","created_at":"2026-05-18T12:32:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:2M3DKFUUPIZSLDJMF4HSPENJLH","target":"record","payload":{"canonical_record":{"source":{"id":"1811.07490","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-11-19T04:07:49Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6729f94c019cdfb6cadc192d08a945321bf8e64bdd5baf544463e99a49541c12","abstract_canon_sha256":"9936a3c04a31d087a5d8f0e577ced468f2247f566ebd5a6fbfa8fd7f38f875fa"},"schema_version":"1.0"},"canonical_sha256":"d3363516947a33258d2c2f0f2791a959f9e0d385025d5799e66f8ed2214efaa8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:06.387826Z","signature_b64":"rNuas3jX+xXmwZBVwWcYWDFr1Rc/aWss/vU3xqEVoaCK8XLzhqXV19CKgr9VLrzfZYISRNM8aZULG7bGJT9AAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d3363516947a33258d2c2f0f2791a959f9e0d385025d5799e66f8ed2214efaa8","last_reissued_at":"2026-05-17T23:48:06.387344Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:06.387344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.07490","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:48:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MianTwqn/luw9/YCULjpy7ZSws+7BG/YUT4T4Jy4Lb9E/K4fI6VN5+3q68cvv5auIADtawwjjVCpTPX0pkbdBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T22:28:56.469029Z"},"content_sha256":"a8692d7c8fee194094a2f5f0e9c5d638681722c5cfdee7f132dfe6448b232114","schema_version":"1.0","event_id":"sha256:a8692d7c8fee194094a2f5f0e9c5d638681722c5cfdee7f132dfe6448b232114"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:2M3DKFUUPIZSLDJMF4HSPENJLH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Hongyu Zhu, Jianjin Zhang, Jianmin Wang, Mingsheng Long, Philip S Yu, Yunbo Wang","submitted_at":"2018-11-19T04:07:49Z","abstract_excerpt":"Natural spatiotemporal processes can be highly non-stationary in many ways, e.g. the low-level non-stationarity such as spatial correlations or temporal dependencies of local pixel values; and the high-level variations such as the accumulation, deformation or dissipation of radar echoes in precipitation forecasting. From Cramer's Decomposition, any non-stationary process can be decomposed into deterministic, time-variant polynomials, plus a zero-mean stochastic term. By applying differencing operations appropriately, we may turn time-variant polynomials into a constant, making the deterministi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.07490","kind":"arxiv","version":3},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:48:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LecOfZdBZOc2F8Btpl5Q8+D6lWxg5Mx6Jb8N3vbWDAK4k0C1J0btuffx58G7M3y8jN7ZNE987K6PwyaX2E6eCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T22:28:56.469471Z"},"content_sha256":"f406e2c91215190a01d4b739e9f93dfa9f95322f8f7429d2da845083f61e41d6","schema_version":"1.0","event_id":"sha256:f406e2c91215190a01d4b739e9f93dfa9f95322f8f7429d2da845083f61e41d6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2M3DKFUUPIZSLDJMF4HSPENJLH/bundle.json","state_url":"https://pith.science/pith/2M3DKFUUPIZSLDJMF4HSPENJLH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2M3DKFUUPIZSLDJMF4HSPENJLH/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":"2026-05-23T22:28:56Z","links":{"resolver":"https://pith.science/pith/2M3DKFUUPIZSLDJMF4HSPENJLH","bundle":"https://pith.science/pith/2M3DKFUUPIZSLDJMF4HSPENJLH/bundle.json","state":"https://pith.science/pith/2M3DKFUUPIZSLDJMF4HSPENJLH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2M3DKFUUPIZSLDJMF4HSPENJLH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:2M3DKFUUPIZSLDJMF4HSPENJLH","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":"9936a3c04a31d087a5d8f0e577ced468f2247f566ebd5a6fbfa8fd7f38f875fa","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-11-19T04:07:49Z","title_canon_sha256":"6729f94c019cdfb6cadc192d08a945321bf8e64bdd5baf544463e99a49541c12"},"schema_version":"1.0","source":{"id":"1811.07490","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.07490","created_at":"2026-05-17T23:48:06Z"},{"alias_kind":"arxiv_version","alias_value":"1811.07490v3","created_at":"2026-05-17T23:48:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.07490","created_at":"2026-05-17T23:48:06Z"},{"alias_kind":"pith_short_12","alias_value":"2M3DKFUUPIZS","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"2M3DKFUUPIZSLDJM","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"2M3DKFUU","created_at":"2026-05-18T12:32:02Z"}],"graph_snapshots":[{"event_id":"sha256:f406e2c91215190a01d4b739e9f93dfa9f95322f8f7429d2da845083f61e41d6","target":"graph","created_at":"2026-05-17T23:48:06Z","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"},"paper":{"abstract_excerpt":"Natural spatiotemporal processes can be highly non-stationary in many ways, e.g. the low-level non-stationarity such as spatial correlations or temporal dependencies of local pixel values; and the high-level variations such as the accumulation, deformation or dissipation of radar echoes in precipitation forecasting. From Cramer's Decomposition, any non-stationary process can be decomposed into deterministic, time-variant polynomials, plus a zero-mean stochastic term. By applying differencing operations appropriately, we may turn time-variant polynomials into a constant, making the deterministi","authors_text":"Hongyu Zhu, Jianjin Zhang, Jianmin Wang, Mingsheng Long, Philip S Yu, Yunbo Wang","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-11-19T04:07:49Z","title":"Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.07490","kind":"arxiv","version":3},"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:a8692d7c8fee194094a2f5f0e9c5d638681722c5cfdee7f132dfe6448b232114","target":"record","created_at":"2026-05-17T23:48:06Z","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":"9936a3c04a31d087a5d8f0e577ced468f2247f566ebd5a6fbfa8fd7f38f875fa","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-11-19T04:07:49Z","title_canon_sha256":"6729f94c019cdfb6cadc192d08a945321bf8e64bdd5baf544463e99a49541c12"},"schema_version":"1.0","source":{"id":"1811.07490","kind":"arxiv","version":3}},"canonical_sha256":"d3363516947a33258d2c2f0f2791a959f9e0d385025d5799e66f8ed2214efaa8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d3363516947a33258d2c2f0f2791a959f9e0d385025d5799e66f8ed2214efaa8","first_computed_at":"2026-05-17T23:48:06.387344Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:06.387344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rNuas3jX+xXmwZBVwWcYWDFr1Rc/aWss/vU3xqEVoaCK8XLzhqXV19CKgr9VLrzfZYISRNM8aZULG7bGJT9AAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:06.387826Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.07490","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a8692d7c8fee194094a2f5f0e9c5d638681722c5cfdee7f132dfe6448b232114","sha256:f406e2c91215190a01d4b739e9f93dfa9f95322f8f7429d2da845083f61e41d6"],"state_sha256":"5d70b5b64badcb4670a3d99cf8ebf49d003ff1a8c6c4a98e405c913ddc91ba4c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"grsveHt6Ue3BaWvh6METFWSwC7vlhHebKnloUWF24bIvENES3tQ7XjvH2qMYpWnE1I3/6hcZGDfXBOWNbEvJBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T22:28:56.472678Z","bundle_sha256":"ddbf36d9cdcb7f8151dfc58312208972e1710e21c11b0d43ce26fa4d697bb750"}}