{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:YJHNX6YWGNMSWFW7JKUK3GETO5","short_pith_number":"pith:YJHNX6YW","canonical_record":{"source":{"id":"1911.00102","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2019-10-31T20:55:08Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"d3fe4d9b7edc4b9e6c7282abb71ff5392fe9978bfd54d81695cde0f12b29a5b1","abstract_canon_sha256":"29955acb7ed27ab3b4a6ce3c1107c2fe3fef32555be7bd73b9337adc50db511c"},"schema_version":"1.0"},"canonical_sha256":"c24edbfb1633592b16df4aa8ad989377509167e870fcae8f0161014e9b336301","source":{"kind":"arxiv","id":"1911.00102","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.00102","created_at":"2026-07-05T00:16:23Z"},{"alias_kind":"arxiv_version","alias_value":"1911.00102v1","created_at":"2026-07-05T00:16:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.00102","created_at":"2026-07-05T00:16:23Z"},{"alias_kind":"pith_short_12","alias_value":"YJHNX6YWGNMS","created_at":"2026-07-05T00:16:23Z"},{"alias_kind":"pith_short_16","alias_value":"YJHNX6YWGNMSWFW7","created_at":"2026-07-05T00:16:23Z"},{"alias_kind":"pith_short_8","alias_value":"YJHNX6YW","created_at":"2026-07-05T00:16:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:YJHNX6YWGNMSWFW7JKUK3GETO5","target":"record","payload":{"canonical_record":{"source":{"id":"1911.00102","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2019-10-31T20:55:08Z","cross_cats_sorted":["eess.AS"],"title_canon_sha256":"d3fe4d9b7edc4b9e6c7282abb71ff5392fe9978bfd54d81695cde0f12b29a5b1","abstract_canon_sha256":"29955acb7ed27ab3b4a6ce3c1107c2fe3fef32555be7bd73b9337adc50db511c"},"schema_version":"1.0"},"canonical_sha256":"c24edbfb1633592b16df4aa8ad989377509167e870fcae8f0161014e9b336301","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:16:23.528018Z","signature_b64":"U82feGQu1LpkLalWhl0h8uiIn8KF1cJBrVagoGTr9OPg3f/zNCyRkefgmJehLN4G2djFvqo64P7doVXl3oEYDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c24edbfb1633592b16df4aa8ad989377509167e870fcae8f0161014e9b336301","last_reissued_at":"2026-07-05T00:16:23.527671Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:16:23.527671Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1911.00102","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":"2026-07-05T00:16:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H1ex4l+1hQ05+9sQj4Lx7NfvGrfwGBTKW+A0SNuNyriN/h6hTszD9uFSZFouVskvzn/u5BCTI0mQqKTUPkLKDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T22:46:53.794012Z"},"content_sha256":"04af1e5e0b918bf27ae53f828e7171c580bb0fc882596c111fe2d28e97b65045","schema_version":"1.0","event_id":"sha256:04af1e5e0b918bf27ae53f828e7171c580bb0fc882596c111fe2d28e97b65045"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:YJHNX6YWGNMSWFW7JKUK3GETO5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"End-to-end Non-Negative Autoencoders for Sound Source Separation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.AS"],"primary_cat":"cs.SD","authors_text":"Efthymios Tzinis, Paris Smaragdis, Shrikant Venkataramani","submitted_at":"2019-10-31T20:55:08Z","abstract_excerpt":"Discriminative models for source separation have recently been shown to produce impressive results. However, when operating on sources outside of the training set, these models can not perform as well and are cumbersome to update. Classical methods like Non-negative Matrix Factorization (NMF) provide modular approaches to source separation that can be easily updated to adapt to new mixture scenarios. In this paper, we generalize NMF to develop end-to-end non-negative auto-encoders and demonstrate how they can be used for source separation. Our experiments indicate that these models deliver com"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.00102","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1911.00102/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":"2026-07-05T00:16:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wagoBzL5ZE/DnoYWA8zgLmVmagAkQvUph8bh0tgybOsB1txLMMw7uoBK+b7diSyoXIoPJ5h3u6wc3hWWvobgAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T22:46:53.794638Z"},"content_sha256":"d19c04c778a8eb9ad8a5c2c728b15399c30fd1db0b11b2db7136999b42342dae","schema_version":"1.0","event_id":"sha256:d19c04c778a8eb9ad8a5c2c728b15399c30fd1db0b11b2db7136999b42342dae"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YJHNX6YWGNMSWFW7JKUK3GETO5/bundle.json","state_url":"https://pith.science/pith/YJHNX6YWGNMSWFW7JKUK3GETO5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YJHNX6YWGNMSWFW7JKUK3GETO5/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":"2026-08-17T22:46:53Z","links":{"resolver":"https://pith.science/pith/YJHNX6YWGNMSWFW7JKUK3GETO5","bundle":"https://pith.science/pith/YJHNX6YWGNMSWFW7JKUK3GETO5/bundle.json","state":"https://pith.science/pith/YJHNX6YWGNMSWFW7JKUK3GETO5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YJHNX6YWGNMSWFW7JKUK3GETO5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:YJHNX6YWGNMSWFW7JKUK3GETO5","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":"29955acb7ed27ab3b4a6ce3c1107c2fe3fef32555be7bd73b9337adc50db511c","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2019-10-31T20:55:08Z","title_canon_sha256":"d3fe4d9b7edc4b9e6c7282abb71ff5392fe9978bfd54d81695cde0f12b29a5b1"},"schema_version":"1.0","source":{"id":"1911.00102","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.00102","created_at":"2026-07-05T00:16:23Z"},{"alias_kind":"arxiv_version","alias_value":"1911.00102v1","created_at":"2026-07-05T00:16:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.00102","created_at":"2026-07-05T00:16:23Z"},{"alias_kind":"pith_short_12","alias_value":"YJHNX6YWGNMS","created_at":"2026-07-05T00:16:23Z"},{"alias_kind":"pith_short_16","alias_value":"YJHNX6YWGNMSWFW7","created_at":"2026-07-05T00:16:23Z"},{"alias_kind":"pith_short_8","alias_value":"YJHNX6YW","created_at":"2026-07-05T00:16:23Z"}],"graph_snapshots":[{"event_id":"sha256:d19c04c778a8eb9ad8a5c2c728b15399c30fd1db0b11b2db7136999b42342dae","target":"graph","created_at":"2026-07-05T00:16:23Z","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/1911.00102/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Discriminative models for source separation have recently been shown to produce impressive results. However, when operating on sources outside of the training set, these models can not perform as well and are cumbersome to update. Classical methods like Non-negative Matrix Factorization (NMF) provide modular approaches to source separation that can be easily updated to adapt to new mixture scenarios. In this paper, we generalize NMF to develop end-to-end non-negative auto-encoders and demonstrate how they can be used for source separation. Our experiments indicate that these models deliver com","authors_text":"Efthymios Tzinis, Paris Smaragdis, Shrikant Venkataramani","cross_cats":["eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2019-10-31T20:55:08Z","title":"End-to-end Non-Negative Autoencoders for Sound Source Separation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.00102","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":"sha256:04af1e5e0b918bf27ae53f828e7171c580bb0fc882596c111fe2d28e97b65045","target":"record","created_at":"2026-07-05T00:16:23Z","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":"29955acb7ed27ab3b4a6ce3c1107c2fe3fef32555be7bd73b9337adc50db511c","cross_cats_sorted":["eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2019-10-31T20:55:08Z","title_canon_sha256":"d3fe4d9b7edc4b9e6c7282abb71ff5392fe9978bfd54d81695cde0f12b29a5b1"},"schema_version":"1.0","source":{"id":"1911.00102","kind":"arxiv","version":1}},"canonical_sha256":"c24edbfb1633592b16df4aa8ad989377509167e870fcae8f0161014e9b336301","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c24edbfb1633592b16df4aa8ad989377509167e870fcae8f0161014e9b336301","first_computed_at":"2026-07-05T00:16:23.527671Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:16:23.527671Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"U82feGQu1LpkLalWhl0h8uiIn8KF1cJBrVagoGTr9OPg3f/zNCyRkefgmJehLN4G2djFvqo64P7doVXl3oEYDw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:16:23.528018Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.00102","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:04af1e5e0b918bf27ae53f828e7171c580bb0fc882596c111fe2d28e97b65045","sha256:d19c04c778a8eb9ad8a5c2c728b15399c30fd1db0b11b2db7136999b42342dae"],"state_sha256":"67d6a23644af79b0cd467da7b56f20a39515cf81ff00b317e27546310028d7a0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bgEXII4RcwnWVCE2f+P/RI9GcUUEXoyuJs/QCB5PaS3Eh/U3UOZ286X552phpom8VawxbaLA0G/pf3/O10RmAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T22:46:53.800138Z","bundle_sha256":"6a76d7ea32396e2c3d334a4248b5f48ae80aed4c7af058324fa4eeb4ac4e0901"}}