{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:2FWLNQRWI3ST7U5M4SXVNVXFQN","short_pith_number":"pith:2FWLNQRW","canonical_record":{"source":{"id":"1608.08266","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2016-08-29T22:10:17Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b0a8991702188b76c941e65fee554bafca1cb1d216617fcce9b4e3515519c239","abstract_canon_sha256":"7e57baa9fe7a544d497d0f175654b9ec051224ba58d635aad8ca87c331e2b0cb"},"schema_version":"1.0"},"canonical_sha256":"d16cb6c23646e53fd3ace4af56d6e5837f260c88dd945c6df648dc1ae7450e47","source":{"kind":"arxiv","id":"1608.08266","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1608.08266","created_at":"2026-05-18T00:07:23Z"},{"alias_kind":"arxiv_version","alias_value":"1608.08266v2","created_at":"2026-05-18T00:07:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.08266","created_at":"2026-05-18T00:07:23Z"},{"alias_kind":"pith_short_12","alias_value":"2FWLNQRWI3ST","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_16","alias_value":"2FWLNQRWI3ST7U5M","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_8","alias_value":"2FWLNQRW","created_at":"2026-05-18T12:29:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:2FWLNQRWI3ST7U5M4SXVNVXFQN","target":"record","payload":{"canonical_record":{"source":{"id":"1608.08266","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2016-08-29T22:10:17Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b0a8991702188b76c941e65fee554bafca1cb1d216617fcce9b4e3515519c239","abstract_canon_sha256":"7e57baa9fe7a544d497d0f175654b9ec051224ba58d635aad8ca87c331e2b0cb"},"schema_version":"1.0"},"canonical_sha256":"d16cb6c23646e53fd3ace4af56d6e5837f260c88dd945c6df648dc1ae7450e47","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:07:23.944913Z","signature_b64":"bDy5qrqOJ6JDdVcEJsG753n03W0tjN6eUO8T8KOk7nezzSnqPw/dh+l/CFKGzssmh8TyAENSNvgNgH26hEOmBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d16cb6c23646e53fd3ace4af56d6e5837f260c88dd945c6df648dc1ae7450e47","last_reissued_at":"2026-05-18T00:07:23.944492Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:07:23.944492Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1608.08266","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:07:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7pp3+zaCHy19EeM3y8QD7coHnAtGndPMDbodZ4n8MJYJbpTLD7tPZjtujaWclsNz42DzV2ENvvaSDqKkNc6jAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T08:55:38.882139Z"},"content_sha256":"71e950b2d59bdd4209b172ce3d51aa99f7b692015e6055a0b2e941090382949a","schema_version":"1.0","event_id":"sha256:71e950b2d59bdd4209b172ce3d51aa99f7b692015e6055a0b2e941090382949a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:2FWLNQRWI3ST7U5M4SXVNVXFQN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Visualizing and Understanding Sum-Product Networks","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Antonio Vergari, Floriana Esposito, Nicola Di Mauro","submitted_at":"2016-08-29T22:10:17Z","abstract_excerpt":"Sum-Product Networks (SPNs) are recently introduced deep tractable probabilistic models by which several kinds of inference queries can be answered exactly and in a tractable time. Up to now, they have been largely used as black box density estimators, assessed only by comparing their likelihood scores only. In this paper we explore and exploit the inner representations learned by SPNs. We do this with a threefold aim: first we want to get a better understanding of the inner workings of SPNs; secondly, we seek additional ways to evaluate one SPN model and compare it against other probabilistic"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.08266","kind":"arxiv","version":2},"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":"2026-05-18T00:07:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Nilc2Y/6UN1Gq3cpiJelbKcNIQroTpSicrJflxza2inHv7LAw08CkukQg440ZniG8N62vDHBsb3eLzCyaNOkAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T08:55:38.882494Z"},"content_sha256":"f057e86e3972134ac591d237caa7c2b286c63b7d3d0ae55a833e765f5ec5fede","schema_version":"1.0","event_id":"sha256:f057e86e3972134ac591d237caa7c2b286c63b7d3d0ae55a833e765f5ec5fede"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2FWLNQRWI3ST7U5M4SXVNVXFQN/bundle.json","state_url":"https://pith.science/pith/2FWLNQRWI3ST7U5M4SXVNVXFQN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2FWLNQRWI3ST7U5M4SXVNVXFQN/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":"2026-06-27T08:55:38Z","links":{"resolver":"https://pith.science/pith/2FWLNQRWI3ST7U5M4SXVNVXFQN","bundle":"https://pith.science/pith/2FWLNQRWI3ST7U5M4SXVNVXFQN/bundle.json","state":"https://pith.science/pith/2FWLNQRWI3ST7U5M4SXVNVXFQN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2FWLNQRWI3ST7U5M4SXVNVXFQN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:2FWLNQRWI3ST7U5M4SXVNVXFQN","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":"7e57baa9fe7a544d497d0f175654b9ec051224ba58d635aad8ca87c331e2b0cb","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2016-08-29T22:10:17Z","title_canon_sha256":"b0a8991702188b76c941e65fee554bafca1cb1d216617fcce9b4e3515519c239"},"schema_version":"1.0","source":{"id":"1608.08266","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1608.08266","created_at":"2026-05-18T00:07:23Z"},{"alias_kind":"arxiv_version","alias_value":"1608.08266v2","created_at":"2026-05-18T00:07:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.08266","created_at":"2026-05-18T00:07:23Z"},{"alias_kind":"pith_short_12","alias_value":"2FWLNQRWI3ST","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_16","alias_value":"2FWLNQRWI3ST7U5M","created_at":"2026-05-18T12:29:55Z"},{"alias_kind":"pith_short_8","alias_value":"2FWLNQRW","created_at":"2026-05-18T12:29:55Z"}],"graph_snapshots":[{"event_id":"sha256:f057e86e3972134ac591d237caa7c2b286c63b7d3d0ae55a833e765f5ec5fede","target":"graph","created_at":"2026-05-18T00:07:23Z","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"},"paper":{"abstract_excerpt":"Sum-Product Networks (SPNs) are recently introduced deep tractable probabilistic models by which several kinds of inference queries can be answered exactly and in a tractable time. Up to now, they have been largely used as black box density estimators, assessed only by comparing their likelihood scores only. In this paper we explore and exploit the inner representations learned by SPNs. We do this with a threefold aim: first we want to get a better understanding of the inner workings of SPNs; secondly, we seek additional ways to evaluate one SPN model and compare it against other probabilistic","authors_text":"Antonio Vergari, Floriana Esposito, Nicola Di Mauro","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2016-08-29T22:10:17Z","title":"Visualizing and Understanding Sum-Product Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.08266","kind":"arxiv","version":2},"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":"sha256:71e950b2d59bdd4209b172ce3d51aa99f7b692015e6055a0b2e941090382949a","target":"record","created_at":"2026-05-18T00:07:23Z","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":"7e57baa9fe7a544d497d0f175654b9ec051224ba58d635aad8ca87c331e2b0cb","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2016-08-29T22:10:17Z","title_canon_sha256":"b0a8991702188b76c941e65fee554bafca1cb1d216617fcce9b4e3515519c239"},"schema_version":"1.0","source":{"id":"1608.08266","kind":"arxiv","version":2}},"canonical_sha256":"d16cb6c23646e53fd3ace4af56d6e5837f260c88dd945c6df648dc1ae7450e47","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d16cb6c23646e53fd3ace4af56d6e5837f260c88dd945c6df648dc1ae7450e47","first_computed_at":"2026-05-18T00:07:23.944492Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:07:23.944492Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bDy5qrqOJ6JDdVcEJsG753n03W0tjN6eUO8T8KOk7nezzSnqPw/dh+l/CFKGzssmh8TyAENSNvgNgH26hEOmBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:07:23.944913Z","signed_message":"canonical_sha256_bytes"},"source_id":"1608.08266","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:71e950b2d59bdd4209b172ce3d51aa99f7b692015e6055a0b2e941090382949a","sha256:f057e86e3972134ac591d237caa7c2b286c63b7d3d0ae55a833e765f5ec5fede"],"state_sha256":"e3d849556cbf374847f56ae1b118c9487b1f321c0c53bfbeb1922eaf13429967"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JR7/QEZt45XSmX62x/S2fkvLWRxhFboq85JhnwvANKdiNPSDXInp4iAz4OgLr9MUTscoepjApOTVfsqda+/4CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T08:55:38.884312Z","bundle_sha256":"e7de1412b70ecb6cc68ecff26af6774dab8bd795c9d8ef58d7581d24b091698b"}}