{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:K6PEHQJPIQ3RJD4ODHMSX3PPZA","short_pith_number":"pith:K6PEHQJP","canonical_record":{"source":{"id":"1601.06403","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-01-24T15:59:44Z","cross_cats_sorted":["cs.CV","math.IT","stat.ML"],"title_canon_sha256":"67024e83d95132b4b7bd2589821ec8fc910464466685d22cee8295c93658fd09","abstract_canon_sha256":"17357b93da748cf9cbbc1ce81dfb72a7e5fc19a458aa1eb28dc1a87175ca9da4"},"schema_version":"1.0"},"canonical_sha256":"579e43c12f4437148f8e19d92bedefc8031b6e77e4ec7c73f5d4554b6d153ade","source":{"kind":"arxiv","id":"1601.06403","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1601.06403","created_at":"2026-05-18T01:11:21Z"},{"alias_kind":"arxiv_version","alias_value":"1601.06403v5","created_at":"2026-05-18T01:11:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1601.06403","created_at":"2026-05-18T01:11:21Z"},{"alias_kind":"pith_short_12","alias_value":"K6PEHQJPIQ3R","created_at":"2026-05-18T12:30:25Z"},{"alias_kind":"pith_short_16","alias_value":"K6PEHQJPIQ3RJD4O","created_at":"2026-05-18T12:30:25Z"},{"alias_kind":"pith_short_8","alias_value":"K6PEHQJP","created_at":"2026-05-18T12:30:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:K6PEHQJPIQ3RJD4ODHMSX3PPZA","target":"record","payload":{"canonical_record":{"source":{"id":"1601.06403","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-01-24T15:59:44Z","cross_cats_sorted":["cs.CV","math.IT","stat.ML"],"title_canon_sha256":"67024e83d95132b4b7bd2589821ec8fc910464466685d22cee8295c93658fd09","abstract_canon_sha256":"17357b93da748cf9cbbc1ce81dfb72a7e5fc19a458aa1eb28dc1a87175ca9da4"},"schema_version":"1.0"},"canonical_sha256":"579e43c12f4437148f8e19d92bedefc8031b6e77e4ec7c73f5d4554b6d153ade","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:11:21.543593Z","signature_b64":"tMBjgkNrgjYuJyGWiAYDWjEromHsasGyEaChsMM59rzvILsCGjmCraeIVnvSU9w6WROl/Mg3ZgwwqsjU2UrlAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"579e43c12f4437148f8e19d92bedefc8031b6e77e4ec7c73f5d4554b6d153ade","last_reissued_at":"2026-05-18T01:11:21.543071Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:11:21.543071Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1601.06403","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:11:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TM8+GLX5VNFuhvq/iQI6HAXbJ2Idp1wzqvzmFu7CZCbNxo566YFFMALb19stxMhriPCG/LKVPDYTU5XpB6kRDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T21:05:02.345610Z"},"content_sha256":"45191fb7fe8dae1357aa4d1829459bb72cc583bfb84850407a40fcaa60b5220c","schema_version":"1.0","event_id":"sha256:45191fb7fe8dae1357aa4d1829459bb72cc583bfb84850407a40fcaa60b5220c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:K6PEHQJPIQ3RJD4ODHMSX3PPZA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Synthesis of Gaussian Trees with Correlation Sign Ambiguity: An Information Theoretic Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","math.IT","stat.ML"],"primary_cat":"cs.IT","authors_text":"Ali Moharrer, George T. Amariucai, Jing Deng, Shuangqing Wei","submitted_at":"2016-01-24T15:59:44Z","abstract_excerpt":"In latent Gaussian trees the pairwise correlation signs between the variables are intrinsically unrecoverable. Such information is vital since it completely determines the direction in which two variables are associated. In this work, we resort to information theoretical approaches to achieve two fundamental goals: First, we quantify the amount of information loss due to unrecoverable sign information. Second, we show the importance of such information in determining the maximum achievable rate region, in which the observed output vector can be synthesized, given its probability density functi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1601.06403","kind":"arxiv","version":5},"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":"2026-05-18T01:11:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dS0OnIqYYt1Q3nekE0aFuOrfFlzh0jUmnEA3XTZQwTB8K4KIVSgKHZKj9pIYEHy/3R14+qTarwnqlVw+bmnnAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T21:05:02.345950Z"},"content_sha256":"1aff22b4add2dc830a869f03ab9fc9b5881670137706a6dd28f4797b27e67e32","schema_version":"1.0","event_id":"sha256:1aff22b4add2dc830a869f03ab9fc9b5881670137706a6dd28f4797b27e67e32"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/K6PEHQJPIQ3RJD4ODHMSX3PPZA/bundle.json","state_url":"https://pith.science/pith/K6PEHQJPIQ3RJD4ODHMSX3PPZA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/K6PEHQJPIQ3RJD4ODHMSX3PPZA/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":"2026-06-24T21:05:02Z","links":{"resolver":"https://pith.science/pith/K6PEHQJPIQ3RJD4ODHMSX3PPZA","bundle":"https://pith.science/pith/K6PEHQJPIQ3RJD4ODHMSX3PPZA/bundle.json","state":"https://pith.science/pith/K6PEHQJPIQ3RJD4ODHMSX3PPZA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/K6PEHQJPIQ3RJD4ODHMSX3PPZA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:K6PEHQJPIQ3RJD4ODHMSX3PPZA","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":"17357b93da748cf9cbbc1ce81dfb72a7e5fc19a458aa1eb28dc1a87175ca9da4","cross_cats_sorted":["cs.CV","math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-01-24T15:59:44Z","title_canon_sha256":"67024e83d95132b4b7bd2589821ec8fc910464466685d22cee8295c93658fd09"},"schema_version":"1.0","source":{"id":"1601.06403","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1601.06403","created_at":"2026-05-18T01:11:21Z"},{"alias_kind":"arxiv_version","alias_value":"1601.06403v5","created_at":"2026-05-18T01:11:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1601.06403","created_at":"2026-05-18T01:11:21Z"},{"alias_kind":"pith_short_12","alias_value":"K6PEHQJPIQ3R","created_at":"2026-05-18T12:30:25Z"},{"alias_kind":"pith_short_16","alias_value":"K6PEHQJPIQ3RJD4O","created_at":"2026-05-18T12:30:25Z"},{"alias_kind":"pith_short_8","alias_value":"K6PEHQJP","created_at":"2026-05-18T12:30:25Z"}],"graph_snapshots":[{"event_id":"sha256:1aff22b4add2dc830a869f03ab9fc9b5881670137706a6dd28f4797b27e67e32","target":"graph","created_at":"2026-05-18T01:11:21Z","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":"In latent Gaussian trees the pairwise correlation signs between the variables are intrinsically unrecoverable. Such information is vital since it completely determines the direction in which two variables are associated. In this work, we resort to information theoretical approaches to achieve two fundamental goals: First, we quantify the amount of information loss due to unrecoverable sign information. Second, we show the importance of such information in determining the maximum achievable rate region, in which the observed output vector can be synthesized, given its probability density functi","authors_text":"Ali Moharrer, George T. Amariucai, Jing Deng, Shuangqing Wei","cross_cats":["cs.CV","math.IT","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-01-24T15:59:44Z","title":"Synthesis of Gaussian Trees with Correlation Sign Ambiguity: An Information Theoretic Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1601.06403","kind":"arxiv","version":5},"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":"sha256:45191fb7fe8dae1357aa4d1829459bb72cc583bfb84850407a40fcaa60b5220c","target":"record","created_at":"2026-05-18T01:11:21Z","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":"17357b93da748cf9cbbc1ce81dfb72a7e5fc19a458aa1eb28dc1a87175ca9da4","cross_cats_sorted":["cs.CV","math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-01-24T15:59:44Z","title_canon_sha256":"67024e83d95132b4b7bd2589821ec8fc910464466685d22cee8295c93658fd09"},"schema_version":"1.0","source":{"id":"1601.06403","kind":"arxiv","version":5}},"canonical_sha256":"579e43c12f4437148f8e19d92bedefc8031b6e77e4ec7c73f5d4554b6d153ade","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"579e43c12f4437148f8e19d92bedefc8031b6e77e4ec7c73f5d4554b6d153ade","first_computed_at":"2026-05-18T01:11:21.543071Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:11:21.543071Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tMBjgkNrgjYuJyGWiAYDWjEromHsasGyEaChsMM59rzvILsCGjmCraeIVnvSU9w6WROl/Mg3ZgwwqsjU2UrlAA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:11:21.543593Z","signed_message":"canonical_sha256_bytes"},"source_id":"1601.06403","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:45191fb7fe8dae1357aa4d1829459bb72cc583bfb84850407a40fcaa60b5220c","sha256:1aff22b4add2dc830a869f03ab9fc9b5881670137706a6dd28f4797b27e67e32"],"state_sha256":"e32907864714962b4db211e4d8c3e86f4628b9dd537a043b630ca26d13a99821"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4D029CBOkt8dl2QTjF3RnuD0SQ3lfOieJ2nmaQ4qups1ax1FbcF3VlQR84mTvMheVrbGo0QsKeP+2++YFm4xAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-24T21:05:02.347906Z","bundle_sha256":"bbc9bf375ce0939b221b8a1530f07019bab0880b39fe710aa53e1ab6d1a2b3b7"}}