{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:CCSODOTVC6CTAJTWTLPQ2ALGUD","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":"c9decdf03729946d02dcbae644aea276375fcad8ae6a4fb8d619c4f1503e4267","cross_cats_sorted":["cs.AI","cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-23T07:48:00Z","title_canon_sha256":"15b426b914a8c0a5b33c968abc786523b32a83a7874e1824221a383a475dea62"},"schema_version":"1.0","source":{"id":"2405.14270","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.14270","created_at":"2026-07-05T08:22:12Z"},{"alias_kind":"arxiv_version","alias_value":"2405.14270v1","created_at":"2026-07-05T08:22:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.14270","created_at":"2026-07-05T08:22:12Z"},{"alias_kind":"pith_short_12","alias_value":"CCSODOTVC6CT","created_at":"2026-07-05T08:22:12Z"},{"alias_kind":"pith_short_16","alias_value":"CCSODOTVC6CTAJTW","created_at":"2026-07-05T08:22:12Z"},{"alias_kind":"pith_short_8","alias_value":"CCSODOTV","created_at":"2026-07-05T08:22:12Z"}],"graph_snapshots":[{"event_id":"sha256:76e4e7bbbe0e5c2860e0e037c8e15945caeecaff47032a2a9a82627962335c43","target":"graph","created_at":"2026-07-05T08:22:12Z","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/2405.14270/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Scientific datasets present unique challenges for machine learning-driven compression methods, including more stringent requirements on accuracy and mitigation of potential invalidating artifacts. Drawing on results from compressed sensing and rate-distortion theory, we introduce effective data compression methods by developing autoencoders using high dimensional latent spaces that are $L^1$-regularized to obtain sparse low dimensional representations. We show how these information-rich latent spaces can be used to mitigate blurring and other artifacts to obtain highly effective data compressi","authors_text":"Jack Michael Solomon, Matthias Chung, Paul Atzberger, Rick Archibald","cross_cats":["cs.AI","cs.NA","math.NA"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-23T07:48:00Z","title":"Sparse $L^1$-Autoencoders for Scientific Data Compression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.14270","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:ec59f166c76de0d8078720ca9fd98e62071701392c0b893019057aa26c23a8ea","target":"record","created_at":"2026-07-05T08:22:12Z","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":"c9decdf03729946d02dcbae644aea276375fcad8ae6a4fb8d619c4f1503e4267","cross_cats_sorted":["cs.AI","cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-23T07:48:00Z","title_canon_sha256":"15b426b914a8c0a5b33c968abc786523b32a83a7874e1824221a383a475dea62"},"schema_version":"1.0","source":{"id":"2405.14270","kind":"arxiv","version":1}},"canonical_sha256":"10a4e1ba7517853026769adf0d0166a0e9845bee1dd24d9b5e1db4f7013bb0ff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"10a4e1ba7517853026769adf0d0166a0e9845bee1dd24d9b5e1db4f7013bb0ff","first_computed_at":"2026-07-05T08:22:12.199908Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:22:12.199908Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+9p8tsM8Ff5IK1n+KGQIkt2WUXefl3oXF0HmeUB7FI4IqnzKfLTrgIgnane15yAPwFM7T7Ey2M4M9YvLhXE2Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:22:12.200335Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.14270","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ec59f166c76de0d8078720ca9fd98e62071701392c0b893019057aa26c23a8ea","sha256:76e4e7bbbe0e5c2860e0e037c8e15945caeecaff47032a2a9a82627962335c43"],"state_sha256":"da724d1df4a41a97097f6554cc4ccd92c6cdde66a5374f888c4b783055fbc9e0"}