Showing 201 - 220 results of 441 for search '(( element data algorithm ) OR ((( implement learner algorithm ) OR ( neural coding algorithm ))))', query time: 0.37s Refine Results
  1. 201

    <b>Neural Symbolic Vault: Symbolic Species and</b> <b>DNA Co-Encoding Research Bundle v1.0 (A+M[S] Archive)</b> by Jeffrey Siergiej (20937434)

    Published 2025
    “…</p><p><br></p><p dir="ltr"><br></p><p dir="ltr">Categories / Fields of Research (FOR codes):</p><p dir="ltr"><br></p><ul><li>Medical molecular engineering of nucleic acids and proteins</li><li>Genetically modified animals</li><li>Immunogenetics (incl. genetic immunology)</li><li>Symbolic Systems</li><li>Neural Engineering</li><li>Biomedical engineering not elsewhere classified</li><li>Quantum engineering systems (incl. computing and communications)</li></ul><p dir="ltr"><br></p><p dir="ltr"><br></p><p dir="ltr">Keywords:</p><p dir="ltr">Neural Symbolic Vault, symbolic-gene mutation, DNA-symbol compression, AxiomQoreEngine, A+M[S], Symbolic Token Ledger, artificial species generation, quantum DNA encoding, CLU math, mutation history registry, field interaction tracking</p><p dir="ltr"><br></p><p dir="ltr">Funding Statement:</p><p dir="ltr">No public funding declared. …”
  2. 202

    Dendrogram of the stock prices. by Muhammad Hilal Alkhudaydi (21560690)

    Published 2025
    “…For this reason, having a solid understanding of the elements responsible for these uncertainties is absolutely necessary. …”
  3. 203

    Descriptive statistics on stock prices. by Muhammad Hilal Alkhudaydi (21560690)

    Published 2025
    “…For this reason, having a solid understanding of the elements responsible for these uncertainties is absolutely necessary. …”
  4. 204

    Correlation heatmap of the principal components. by Muhammad Hilal Alkhudaydi (21560690)

    Published 2025
    “…For this reason, having a solid understanding of the elements responsible for these uncertainties is absolutely necessary. …”
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    Data Sheet 1_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.csv by Jared Lichtarge (20548571)

    Published 2025
    “…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…”
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    The code for sample size calculation. by Ying Zhou (25031)

    Published 2025
    “…We collected basic clinical data and multimodal ultrasound data from these patients as predictive features, with clinical pregnancy as the predictive label, for model training. …”
  13. 213

    LSTM model’s equations. by Songsong Wang (8088293)

    Published 2025
    “…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”
  14. 214

    Parameter’s interpretation. by Songsong Wang (8088293)

    Published 2025
    “…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”
  15. 215

    The models’ training parameters. by Songsong Wang (8088293)

    Published 2025
    “…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”
  16. 216

    Model’s measure methods. by Songsong Wang (8088293)

    Published 2025
    “…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”
  17. 217

    Association point and relationship. by Songsong Wang (8088293)

    Published 2025
    “…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”
  18. 218

    Periodic Table’s Properties Using Unsupervised Chemometric Methods: Undergraduate Analytical Chemistry Laboratory Exercise by Adrian Gabriel Pereira de Quental (20382423)

    Published 2024
    “…The unsupervised algorithms were able to find “natural” clustering from the periodic table using the data structure without any prior knowledge of the class assignment of the samples. …”
  19. 219

    Periodic Table’s Properties Using Unsupervised Chemometric Methods: Undergraduate Analytical Chemistry Laboratory Exercise by Adrian Gabriel Pereira de Quental (20382423)

    Published 2024
    “…The unsupervised algorithms were able to find “natural” clustering from the periodic table using the data structure without any prior knowledge of the class assignment of the samples. …”
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