{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:TAJ44T4LWPF2OKZPRFPDR2G674","short_pith_number":"pith:TAJ44T4L","canonical_record":{"source":{"id":"1903.03105","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2019-03-06T19:00:02Z","cross_cats_sorted":["astro-ph.IM","cs.LG","eess.SP","gr-qc"],"title_canon_sha256":"0d1a96011d44f62e932ce4b4c11c6aaeeaab3802441cf4f6ff79f5f8baa36d3b","abstract_canon_sha256":"948dbdbb077815200f666a0cb2b812e12e7fbcccccf31a08e20f580aa3efffe1"},"schema_version":"1.0"},"canonical_sha256":"9813ce4f8bb3cba72b2f895e38e8deff228e2ba5e3ee19839a646a865d640b1d","source":{"kind":"arxiv","id":"1903.03105","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.03105","created_at":"2026-05-17T23:45:14Z"},{"alias_kind":"arxiv_version","alias_value":"1903.03105v1","created_at":"2026-05-17T23:45:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.03105","created_at":"2026-05-17T23:45:14Z"},{"alias_kind":"pith_short_12","alias_value":"TAJ44T4LWPF2","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"TAJ44T4LWPF2OKZP","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"TAJ44T4L","created_at":"2026-05-18T12:33:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:TAJ44T4LWPF2OKZPRFPDR2G674","target":"record","payload":{"canonical_record":{"source":{"id":"1903.03105","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2019-03-06T19:00:02Z","cross_cats_sorted":["astro-ph.IM","cs.LG","eess.SP","gr-qc"],"title_canon_sha256":"0d1a96011d44f62e932ce4b4c11c6aaeeaab3802441cf4f6ff79f5f8baa36d3b","abstract_canon_sha256":"948dbdbb077815200f666a0cb2b812e12e7fbcccccf31a08e20f580aa3efffe1"},"schema_version":"1.0"},"canonical_sha256":"9813ce4f8bb3cba72b2f895e38e8deff228e2ba5e3ee19839a646a865d640b1d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:45:14.770274Z","signature_b64":"w+mgJdbcxxBVZPIM8o24QQA3CC8T6RTiSLiEBwdV4LkS0HQg9rJpRUw6EV6bfkgm2reDfYDy0uj0Zh93XQt7CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9813ce4f8bb3cba72b2f895e38e8deff228e2ba5e3ee19839a646a865d640b1d","last_reissued_at":"2026-05-17T23:45:14.769671Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:45:14.769671Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.03105","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:45:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I8PohO24s9RoI4/Gcl3S950XSsIsPnB9bo1p2qVPEFReLQWbgzcMBhYkXpj1seFwVdbM83qbOkcU3rspLIOSCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T07:23:49.925921Z"},"content_sha256":"b7b80cdd49da6fbac3d692a5151a88d612d7ea434a0ca8a24600054e5942401b","schema_version":"1.0","event_id":"sha256:b7b80cdd49da6fbac3d692a5151a88d612d7ea434a0ca8a24600054e5942401b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:TAJ44T4LWPF2OKZPRFPDR2G674","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-Encoders","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.IM","cs.LG","eess.SP","gr-qc"],"primary_cat":"astro-ph.CO","authors_text":"Daniel George, E. A. Huerta, Hongyu Shen, Zhizhen Zhao","submitted_at":"2019-03-06T19:00:02Z","abstract_excerpt":"Denoising of time domain data is a crucial task for many applications such as communication, translation, virtual assistants etc. For this task, a combination of a recurrent neural net (RNNs) with a Denoising Auto-Encoder (DAEs) has shown promising results. However, this combined model is challenged when operating with low signal-to-noise ratio (SNR) data embedded in non-Gaussian and non-stationary noise. To address this issue, we design a novel model, referred to as 'Enhanced Deep Recurrent Denoising Auto-Encoder' (EDRDAE), that incorporates a signal amplifier layer, and applies curriculum le"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.03105","kind":"arxiv","version":1},"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":"2026-05-17T23:45:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3IQmSI4YpAxDvA7QtHU5ASjFzN4zEP9na7McH3iKfVINUUgdoPAAhMoRt71rifQatF9XiLPeWyRG0XvHw9DDAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T07:23:49.926263Z"},"content_sha256":"dff6efef815b28a01d9d88e37d3d3744758b0db8210daef76eb894e2d367eca1","schema_version":"1.0","event_id":"sha256:dff6efef815b28a01d9d88e37d3d3744758b0db8210daef76eb894e2d367eca1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TAJ44T4LWPF2OKZPRFPDR2G674/bundle.json","state_url":"https://pith.science/pith/TAJ44T4LWPF2OKZPRFPDR2G674/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TAJ44T4LWPF2OKZPRFPDR2G674/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":"2026-05-28T07:23:49Z","links":{"resolver":"https://pith.science/pith/TAJ44T4LWPF2OKZPRFPDR2G674","bundle":"https://pith.science/pith/TAJ44T4LWPF2OKZPRFPDR2G674/bundle.json","state":"https://pith.science/pith/TAJ44T4LWPF2OKZPRFPDR2G674/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TAJ44T4LWPF2OKZPRFPDR2G674/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:TAJ44T4LWPF2OKZPRFPDR2G674","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":"948dbdbb077815200f666a0cb2b812e12e7fbcccccf31a08e20f580aa3efffe1","cross_cats_sorted":["astro-ph.IM","cs.LG","eess.SP","gr-qc"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2019-03-06T19:00:02Z","title_canon_sha256":"0d1a96011d44f62e932ce4b4c11c6aaeeaab3802441cf4f6ff79f5f8baa36d3b"},"schema_version":"1.0","source":{"id":"1903.03105","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.03105","created_at":"2026-05-17T23:45:14Z"},{"alias_kind":"arxiv_version","alias_value":"1903.03105v1","created_at":"2026-05-17T23:45:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.03105","created_at":"2026-05-17T23:45:14Z"},{"alias_kind":"pith_short_12","alias_value":"TAJ44T4LWPF2","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"TAJ44T4LWPF2OKZP","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"TAJ44T4L","created_at":"2026-05-18T12:33:27Z"}],"graph_snapshots":[{"event_id":"sha256:dff6efef815b28a01d9d88e37d3d3744758b0db8210daef76eb894e2d367eca1","target":"graph","created_at":"2026-05-17T23:45:14Z","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":"Denoising of time domain data is a crucial task for many applications such as communication, translation, virtual assistants etc. For this task, a combination of a recurrent neural net (RNNs) with a Denoising Auto-Encoder (DAEs) has shown promising results. However, this combined model is challenged when operating with low signal-to-noise ratio (SNR) data embedded in non-Gaussian and non-stationary noise. To address this issue, we design a novel model, referred to as 'Enhanced Deep Recurrent Denoising Auto-Encoder' (EDRDAE), that incorporates a signal amplifier layer, and applies curriculum le","authors_text":"Daniel George, E. A. Huerta, Hongyu Shen, Zhizhen Zhao","cross_cats":["astro-ph.IM","cs.LG","eess.SP","gr-qc"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2019-03-06T19:00:02Z","title":"Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-Encoders"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.03105","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:b7b80cdd49da6fbac3d692a5151a88d612d7ea434a0ca8a24600054e5942401b","target":"record","created_at":"2026-05-17T23:45:14Z","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":"948dbdbb077815200f666a0cb2b812e12e7fbcccccf31a08e20f580aa3efffe1","cross_cats_sorted":["astro-ph.IM","cs.LG","eess.SP","gr-qc"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.CO","submitted_at":"2019-03-06T19:00:02Z","title_canon_sha256":"0d1a96011d44f62e932ce4b4c11c6aaeeaab3802441cf4f6ff79f5f8baa36d3b"},"schema_version":"1.0","source":{"id":"1903.03105","kind":"arxiv","version":1}},"canonical_sha256":"9813ce4f8bb3cba72b2f895e38e8deff228e2ba5e3ee19839a646a865d640b1d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9813ce4f8bb3cba72b2f895e38e8deff228e2ba5e3ee19839a646a865d640b1d","first_computed_at":"2026-05-17T23:45:14.769671Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:45:14.769671Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"w+mgJdbcxxBVZPIM8o24QQA3CC8T6RTiSLiEBwdV4LkS0HQg9rJpRUw6EV6bfkgm2reDfYDy0uj0Zh93XQt7CQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:45:14.770274Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.03105","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b7b80cdd49da6fbac3d692a5151a88d612d7ea434a0ca8a24600054e5942401b","sha256:dff6efef815b28a01d9d88e37d3d3744758b0db8210daef76eb894e2d367eca1"],"state_sha256":"367c2b7de8aac652122cf5d2f1c9ff1242d5c2dfe5340aa7ac2c78312e179af2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j/wClQLNovzKsx91yxaKVqRGI5ygZm3VbE7McY/DJZpa3QDkkXuSTBI/0hf48MquwenxK0PaA8pwpE8sW7KDCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T07:23:49.928260Z","bundle_sha256":"5679245fa1a4d077523cc4aa23ecc2b0142057cdd6166ba7b9739370562595cb"}}