{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:RKC2TFNPWL5VB2NVTBY3OVU4UN","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":"d44288cb4bb2078d92d27398b2ef0b1316df0f8c793dcc2eafba5ef8ce105e1c","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-12-22T14:43:50Z","title_canon_sha256":"48fceabed6db93a9a31f793894ef45046c2c248df03f21516ad804153cabe055"},"schema_version":"1.0","source":{"id":"2012.12056","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.12056","created_at":"2026-07-05T02:01:24Z"},{"alias_kind":"arxiv_version","alias_value":"2012.12056v1","created_at":"2026-07-05T02:01:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.12056","created_at":"2026-07-05T02:01:24Z"},{"alias_kind":"pith_short_12","alias_value":"RKC2TFNPWL5V","created_at":"2026-07-05T02:01:24Z"},{"alias_kind":"pith_short_16","alias_value":"RKC2TFNPWL5VB2NV","created_at":"2026-07-05T02:01:24Z"},{"alias_kind":"pith_short_8","alias_value":"RKC2TFNP","created_at":"2026-07-05T02:01:24Z"}],"graph_snapshots":[{"event_id":"sha256:cecacbea65ca9a346cbd5e6951ae691aaa0f856c02708df3629f9297161a954f","target":"graph","created_at":"2026-07-05T02:01:24Z","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/2012.12056/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"There is an urgent need to build models to tackle Indoor Air Quality issue. Since the model should be accurate and fast, Reduced Order Modelling technique is used to reduce the dimensionality of the problem. The accuracy of the model, that represent a dynamic system, is improved integrating real data coming from sensors using Data Assimilation techniques. In this paper, we formulate a new methodology called Latent Assimilation that combines Data Assimilation and Machine Learning. We use a Convolutional neural network to reduce the dimensionality of the problem, a Long-Short-Term-Memory to buil","authors_text":"Cesar Quilodran Casas, Christopher Pain, Laetitia Mottet, Maddalena Amendola, Paul Linden, Rossella Arcucci, Shiwei Fan, Yi-Ke Guo","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-12-22T14:43:50Z","title":"Data Assimilation in the Latent Space of a Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.12056","kind":"arxiv","version":1},"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":"sha256:51a6bc25315f54d2dfd70459aec1b66b690c2e0ea4328d3c448d9ecd9f627611","target":"record","created_at":"2026-07-05T02:01:24Z","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":"d44288cb4bb2078d92d27398b2ef0b1316df0f8c793dcc2eafba5ef8ce105e1c","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-12-22T14:43:50Z","title_canon_sha256":"48fceabed6db93a9a31f793894ef45046c2c248df03f21516ad804153cabe055"},"schema_version":"1.0","source":{"id":"2012.12056","kind":"arxiv","version":1}},"canonical_sha256":"8a85a995afb2fb50e9b59871b7569ca3692416a663e3c676545a4324359c5438","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8a85a995afb2fb50e9b59871b7569ca3692416a663e3c676545a4324359c5438","first_computed_at":"2026-07-05T02:01:24.188966Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:01:24.188966Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BX1wTM7EYh5bpWW2GjdaWGYgItGBkjyFgVBB3UCtTX+5RjFmZhgfEsg+ixjCcauBLY9wMVG8QColxL0n8dsMDg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:01:24.189412Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.12056","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:51a6bc25315f54d2dfd70459aec1b66b690c2e0ea4328d3c448d9ecd9f627611","sha256:cecacbea65ca9a346cbd5e6951ae691aaa0f856c02708df3629f9297161a954f"],"state_sha256":"91844f247f1516bd99bdd78126811b9398f713a4f35af7568a7c54b3b1af8b6c"}