Dontopedia

LSTM AutoEncoder

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

LSTM AutoEncoder has 23 facts recorded in Dontopedia across 5 references, with 3 live disagreements.

23 facts·15 predicates·5 sources·3 in dispute

Mostly:has f1 score(4), has parameter count(3), has training time(2)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (9)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

hasFewerParametersThanHas Fewer Parameters Than(2)

beatsOnF1Beats on F1(1)

comparesMethodCompares Method(1)

comparesToCompares to(1)

has860TimesFewerParametersThanHas860 Times Fewer Parameters Than(1)

hasParameterCountAdvantageOverHas Parameter Count Advantage Over(1)

matchesAurocOfMatches Auroc of(1)

outperformsInTrainingSpeedOutperforms in Training Speed(1)

Other facts (21)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

21 facts
PredicateValueRef
Has F1 Score0.98[2]
Has F1 Score0.99[3]
Has F1 Score0.98[4]
Has F1 Score0.98[5]
Has Parameter Count100000[2]
Has Parameter Count150000[3]
Has Parameter Count100000[5]
Has Training Timeminutes[2]
Has Training Timeminutes[5]
Has F10.98[1]
Has More Parametersnull[1]
Has Auroc Score0.99[2]
Is Published Baselinenull[2]
Has Parameter Count Lower Bound50000[3]
Has Parameter Count Upper Bound200000[3]
Has Detection Lead Timenot reported[3]
Has F1 Score Lower Bound0.98[3]
Has F1 Score Upper Bound1[3]
Requires Threshold Tuningtrue[3]
Rdf:typeMachine Learning Model[5]
Has Auroc0.99[5]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

hasF1blah/watt-activation/part-509
0.98
hasMoreParametersblah/watt-activation/part-509
null
hasTrainingTimeblah/watt-activation/part-508
minutes
hasF1Scoreblah/watt-activation/part-508
0.98
hasParameterCountblah/watt-activation/part-508
100000
hasAurocScoreblah/watt-activation/part-508
0.99
isPublishedBaselineblah/watt-activation/part-508
null
labelblah/watt-activation/503
LSTM AutoEncoder
hasParameterCountblah/watt-activation/503
150000
hasParameterCountLowerBoundblah/watt-activation/503
50000
hasParameterCountUpperBoundblah/watt-activation/503
200000
hasDetectionLeadTimeblah/watt-activation/503
not reported
hasF1Scoreblah/watt-activation/503
0.99
hasF1ScoreLowerBoundblah/watt-activation/503
0.98
hasF1ScoreUpperBoundblah/watt-activation/503
1
requiresThresholdTuningblah/watt-activation/503
true
hasF1Scoreblah/watt-activation/506
0.98
typeblah/watt-activation/505
ex:MachineLearningModel
labelblah/watt-activation/505
LSTM AutoEncoder
hasParameterCountblah/watt-activation/505
100000
hasF1Scoreblah/watt-activation/505
0.98
hasAUROCblah/watt-activation/505
0.99
hasTrainingTimeblah/watt-activation/505
minutes

References (5)

5 references
  1. [1]Part 5092 facts
    ctx:discord/blah/watt-activation/part-509
  2. [2]Part 5085 facts
    ctx:discord/blah/watt-activation/part-508
  3. [3]5039 facts
    ctx:discord/blah/watt-activation/503
    • full textwatt-activation-503
      text/plain3 KBdoc:agent/watt-activation-503/6b110c88-b7c7-4361-9c52-c715909ba016
      Show excerpt
      [2026-03-22 19:39] xenonfun: ⏺ Here's how CHON compares to published methods on this exact dataset: ``` ┌────────────────┬───────────────────┬─────────────────┬─────────────────────┬──────────────────────┐ │ Method │ Params
  4. [4]5061 fact
    ctx:discord/blah/watt-activation/506
    • full textwatt-activation-506
      text/plain2 KBdoc:agent/watt-activation-506/491a6927-81ff-44b4-967f-83424796e025
      Show excerpt
      [2026-03-22 20:23] xenonfun: ⏺ Interesting — AUROC is identical at 0.985 across all group counts. The residual separability is already maxed out. The F1 differences come from threshold tuning, not the model itself. G=1 actually gives the
  5. [5]5056 facts
    ctx:discord/blah/watt-activation/505
    • full textwatt-activation-505
      text/plain2 KBdoc:agent/watt-activation-505/942386e0-0cb8-490c-8592-6512fb5cc7cb
      Show excerpt
      [2026-03-22 20:11] xenonfun: ``` ⏺ Formal results: ┌───────────────┬───────────────────┬──────────────────────────┐ │ Metric │ CHON (119 params) │ Best Published │ ├───────────────┼───────────────────┼───────────────

See also

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