{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:WZEYXI7HP6AUMK6ZIKSPTWNEK3","short_pith_number":"pith:WZEYXI7H","canonical_record":{"source":{"id":"1808.00523","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-08-01T19:28:03Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"37ce56426cd131e7f8d1fd4b6b45569e475d94e593655c99eceb4895c1a07160","abstract_canon_sha256":"6da1a604f5d074421415598db61938c0bb070a24f866954f98f0e58a8bbab521"},"schema_version":"1.0"},"canonical_sha256":"b6498ba3e77f81462bd942a4f9d9a456dc7de442a4c39cac0e12f5700dd1e9fd","source":{"kind":"arxiv","id":"1808.00523","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.00523","created_at":"2026-05-17T23:50:24Z"},{"alias_kind":"arxiv_version","alias_value":"1808.00523v2","created_at":"2026-05-17T23:50:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.00523","created_at":"2026-05-17T23:50:24Z"},{"alias_kind":"pith_short_12","alias_value":"WZEYXI7HP6AU","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WZEYXI7HP6AUMK6Z","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WZEYXI7H","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:WZEYXI7HP6AUMK6ZIKSPTWNEK3","target":"record","payload":{"canonical_record":{"source":{"id":"1808.00523","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-08-01T19:28:03Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"37ce56426cd131e7f8d1fd4b6b45569e475d94e593655c99eceb4895c1a07160","abstract_canon_sha256":"6da1a604f5d074421415598db61938c0bb070a24f866954f98f0e58a8bbab521"},"schema_version":"1.0"},"canonical_sha256":"b6498ba3e77f81462bd942a4f9d9a456dc7de442a4c39cac0e12f5700dd1e9fd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:50:24.483402Z","signature_b64":"9NaNItSiz+8p7B7KRhYjYUyXbGNjdykiVwnvvTQ1WmXgRZ79L4mD6UVL02H2JqZuXo7QbrM3eU9FP2Ls9G78Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b6498ba3e77f81462bd942a4f9d9a456dc7de442a4c39cac0e12f5700dd1e9fd","last_reissued_at":"2026-05-17T23:50:24.482955Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:50:24.482955Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.00523","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":"2026-05-17T23:50:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YJFZ5g9yp+i5iWkc7aoy8McDYg8+8wmHFd90XFp4k3OAWv7c6XhF0eO6CVh/M1+1Qgke9K029slj+nBbQxtEDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T00:17:13.031443Z"},"content_sha256":"ff1ceeb90f5a6d46a1b89644c025ae02d3dd56d33f1dfaedcffaf025af7649df","schema_version":"1.0","event_id":"sha256:ff1ceeb90f5a6d46a1b89644c025ae02d3dd56d33f1dfaedcffaf025af7649df"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:WZEYXI7HP6AUMK6ZIKSPTWNEK3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Mod-DeepESN: Modular Deep Echo State Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Dhireesha Kudithipudi, Humza Syed, Stuart Burtner, Zachariah Carmichael","submitted_at":"2018-08-01T19:28:03Z","abstract_excerpt":"Neuro-inspired recurrent neural network algorithms, such as echo state networks, are computationally lightweight and thereby map well onto untethered devices. The baseline echo state network algorithms are shown to be efficient in solving small-scale spatio-temporal problems. However, they underperform for complex tasks that are characterized by multi-scale structures. In this research, an intrinsic plasticity-infused modular deep echo state network architecture is proposed to solve complex and multiple timescale temporal tasks. It outperforms state-of-the-art for time series prediction tasks."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.00523","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":"2026-05-17T23:50:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1q14ReB1y83ae3H6UrkyqEiLZ2aJUucQ5RX0g0SqdyolduqAyttH9vmEuUgVQT3nR48M4xFgCg+0ShB4UDbkAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T00:17:13.032147Z"},"content_sha256":"f6df153d2d4a7741b439cb1e4a58151297b77bce9edd5a8abd80a9b123ae05c4","schema_version":"1.0","event_id":"sha256:f6df153d2d4a7741b439cb1e4a58151297b77bce9edd5a8abd80a9b123ae05c4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WZEYXI7HP6AUMK6ZIKSPTWNEK3/bundle.json","state_url":"https://pith.science/pith/WZEYXI7HP6AUMK6ZIKSPTWNEK3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WZEYXI7HP6AUMK6ZIKSPTWNEK3/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":"2026-06-11T00:17:13Z","links":{"resolver":"https://pith.science/pith/WZEYXI7HP6AUMK6ZIKSPTWNEK3","bundle":"https://pith.science/pith/WZEYXI7HP6AUMK6ZIKSPTWNEK3/bundle.json","state":"https://pith.science/pith/WZEYXI7HP6AUMK6ZIKSPTWNEK3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WZEYXI7HP6AUMK6ZIKSPTWNEK3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:WZEYXI7HP6AUMK6ZIKSPTWNEK3","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":"6da1a604f5d074421415598db61938c0bb070a24f866954f98f0e58a8bbab521","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-08-01T19:28:03Z","title_canon_sha256":"37ce56426cd131e7f8d1fd4b6b45569e475d94e593655c99eceb4895c1a07160"},"schema_version":"1.0","source":{"id":"1808.00523","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.00523","created_at":"2026-05-17T23:50:24Z"},{"alias_kind":"arxiv_version","alias_value":"1808.00523v2","created_at":"2026-05-17T23:50:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.00523","created_at":"2026-05-17T23:50:24Z"},{"alias_kind":"pith_short_12","alias_value":"WZEYXI7HP6AU","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WZEYXI7HP6AUMK6Z","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WZEYXI7H","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:f6df153d2d4a7741b439cb1e4a58151297b77bce9edd5a8abd80a9b123ae05c4","target":"graph","created_at":"2026-05-17T23:50:24Z","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":"Neuro-inspired recurrent neural network algorithms, such as echo state networks, are computationally lightweight and thereby map well onto untethered devices. The baseline echo state network algorithms are shown to be efficient in solving small-scale spatio-temporal problems. However, they underperform for complex tasks that are characterized by multi-scale structures. In this research, an intrinsic plasticity-infused modular deep echo state network architecture is proposed to solve complex and multiple timescale temporal tasks. It outperforms state-of-the-art for time series prediction tasks.","authors_text":"Dhireesha Kudithipudi, Humza Syed, Stuart Burtner, Zachariah Carmichael","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-08-01T19:28:03Z","title":"Mod-DeepESN: Modular Deep Echo State Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.00523","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:ff1ceeb90f5a6d46a1b89644c025ae02d3dd56d33f1dfaedcffaf025af7649df","target":"record","created_at":"2026-05-17T23:50:24Z","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":"6da1a604f5d074421415598db61938c0bb070a24f866954f98f0e58a8bbab521","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-08-01T19:28:03Z","title_canon_sha256":"37ce56426cd131e7f8d1fd4b6b45569e475d94e593655c99eceb4895c1a07160"},"schema_version":"1.0","source":{"id":"1808.00523","kind":"arxiv","version":2}},"canonical_sha256":"b6498ba3e77f81462bd942a4f9d9a456dc7de442a4c39cac0e12f5700dd1e9fd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b6498ba3e77f81462bd942a4f9d9a456dc7de442a4c39cac0e12f5700dd1e9fd","first_computed_at":"2026-05-17T23:50:24.482955Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:50:24.482955Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9NaNItSiz+8p7B7KRhYjYUyXbGNjdykiVwnvvTQ1WmXgRZ79L4mD6UVL02H2JqZuXo7QbrM3eU9FP2Ls9G78Ag==","signature_status":"signed_v1","signed_at":"2026-05-17T23:50:24.483402Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.00523","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ff1ceeb90f5a6d46a1b89644c025ae02d3dd56d33f1dfaedcffaf025af7649df","sha256:f6df153d2d4a7741b439cb1e4a58151297b77bce9edd5a8abd80a9b123ae05c4"],"state_sha256":"a458e83bb081560279763e1a84e2eba87547ebd7794364cf813dac1d7e1298fa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"saNEfKKkuwI+r04xoxLHyv6hnbM0Gz/Ow5fleZX9aJSyrv8gGUlmbMQZd+RzYutxHSJvIZzca3KbTsfIG+ExDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T00:17:13.036170Z","bundle_sha256":"e7566f57e9edcb94a0059e794f254ee7ebde34f405b446e5732f44b106912956"}}