Showing 1 - 20 results of 44 for search 'core correction algorithm', query time: 0.26s Refine Results
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    <b>Axiom-Based AGI: A Quantum-Error-Corrected Architecture with Temporal Shard Memory</b> by Lakshit Mathur (20894549)

    Published 2025
    “…<p dir="ltr">This work presents a novel AGI architecture grounded in twelve formal axioms, combining principles from quantum error correction, distributed cognition, and dynamic neural systems. …”
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    On Seeded Subgraph-to-Subgraph Matching: The ssSGM Algorithm and Matchability Information Theory by Lingyao Meng (2327710)

    Published 2025
    “…Then, in the context of a generalized correlated random Bernoulli graph model, in which the pair of graphs naturally have a core of <i>K</i> matched pairs of vertices, we provide and prove mild conditions for the subgraph-subgraph matching problem solution to almost always be the correct <i>K</i> matched pairs of vertices. …”
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    Data and code for: Automatic fish scale analysis by Christian Vogelmann (21646472)

    Published 2025
    “…</p><h3>Includeed in this repository:</h3><ul><li><b>Raw data files:</b></li><li><code>comparison_all_scales.csv</code> – comparison_all_scales.csv - manually verified vs. automated measurements of 1095 coregonid scales</li></ul><ul><li><ul><li><code>Validation_data.csv</code> – manually measured scale data under binocular</li><li><code>Parameter_correction_numeric.csv</code> – calibration data (scale radius vs. fish length/weight)</li></ul></li><li><b>Statistical results:</b></li><li><ul><li><code>comparison_stats_core_variables.csv</code> – verification statistics (bias, relative error, limits of agreement)</li><li><code>Validation_statistics.csv</code> – summary statistics and model fits (manual vs. automated)</li></ul></li><li><b>Executable script (not GUI):</b></li><li><ul><li><code>Algorithm.py</code> – core processing module for scale feature extraction<br>→ <i>Note: The complete Coregon Analyzer application (incl. …”
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    Supplementary file 1_Minimal reduct for propositional circumscription.pdf by Zhongtao Xie (22817600)

    Published 2025
    “…Compared with aspino using glucose as the internal SAT solver and unsatisfiable core analysis technique, our algorithm achieves better CPU time for random and industrial CNF benchmarks, while it is comparable for circuit diagnosis benchmarks.…”