391 to 400 of 877 Results
Mar 14, 2024 -
Replication Data for: On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data
Python Source Code - 3.6 KB -
MD5: 64a069ba31af74b4594737e1033d5165
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Mar 14, 2024 -
Replication Data for: On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data
Plain Text - 101 B -
MD5: 0633ca0ee8f0984d06280aa478107629
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Mar 14, 2024 -
Replication Data for: On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data
Python Source Code - 2.1 KB -
MD5: 41d01fb2260f65f7c13292f558dab154
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Mar 14, 2024 -
Replication Data for: On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data
Python Source Code - 2.1 KB -
MD5: 89a9298ba921e36bd227c3d410ca0fab
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Mar 8, 2024
Advanced learning strategies for potential energy surfaces applied to organic electrolytes |
Mar 8, 2024
Unified diagnostic evaluation of physics-based, data-driven and hybrid hydrological models based on information theory |
Jul 25, 2023 - PN 6-4
Schäfer, Noel; Tilli, Pascal; Munz-Körner, Tanja; Künzel, Sebastian; Vidyapu, Sandeep; Vu, Ngoc Thang; Weiskopf, Daniel, 2023, "Model Parameters and Evaluation Data for our Visual Analysis System for Scene-Graph-Based Visual Question Answering", https://doi.org/10.18419/DARUS-3597, DaRUS, V1
Pretrained model parameters and pregenerated evaluation data for our visual analysis system for scene-graph-based visual question answering (https://doi.org/10.18419/darus-3589). |
Jul 25, 2023 -
Model Parameters and Evaluation Data for our Visual Analysis System for Scene-Graph-Based Visual Question Answering
7Z Archive - 156.9 MB -
MD5: 1900cd3a2a3a6836888073127a4978f5
Pregenerated evaluation data |
Jul 25, 2023 -
Model Parameters and Evaluation Data for our Visual Analysis System for Scene-Graph-Based Visual Question Answering
7Z Archive - 2.5 GB -
MD5: 6521038f236d50fd2d24aad27ca30bb4
Pretrained model parameters |
Jul 25, 2023 - PN 6-4
Munz-Körner, Tanja; Künzel, Sebastian; Weiskopf, Daniel, 2023, "Supplemental Material for "Visual-Explainable AI: The Use Case of Language Models"", https://doi.org/10.18419/DARUS-3456, DaRUS, V1
Supplemental material for the poster "Visual-Explainable AI: The Use Case of Language Models" published at the International Conference on Data-Integrated Simulation Science 2023. Collection of videos and images showing our interactive visualization systems for exploring language models: - Text classification (https://github.com/MunzT/hiddenStatesV... |