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rtm_emulation

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emulation
atmosphere radiative transfer models
hyperspectral
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  1. README.md +5 -19
  2. results/FiLM-Conditioned_Emulator_B1.h5 +0 -3
  3. results/FiLM-Conditioned_Emulator_B2.h5 +0 -3
  4. results/FiLMConditionedEmulator.json +0 -9
  5. results/FiLMConditionedEmulator_A1.h5 +0 -3
  6. results/FiLMConditionedEmulator_B1.h5 +0 -3
  7. results/Krtek.json +9 -0
  8. results/{FiLM-Conditioned_Emulator_A1.h5 → Krtek_A1.h5} +2 -2
  9. results/{FiLMConditionedEmulator_A2.h5 → Krtek_A2.h5} +2 -2
  10. results/{FiLM-Conditioned_Emulator_A2.h5 → Krtek_B1.h5} +2 -2
  11. results/{FiLMConditionedEmulator_B2.h5 → Krtek_B2.h5} +2 -2
  12. results/baseline.json +9 -8
  13. results/baseline_A1.h5 +2 -2
  14. results/baseline_A2.h5 +2 -2
  15. results/baseline_B1.h5 +2 -2
  16. results/baseline_B2.h5 +2 -2
  17. results/metadata.json +0 -9
  18. scenarioA/train/train10000.h5 +0 -3
  19. scenarioB/reference/refInterp.csv +0 -0
README.md CHANGED
@@ -8,15 +8,8 @@ tags:
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  - atmosphere radiative transfer models
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  - hyperspectral
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  pretty_name: Atmospheric Radiative Transfer Emulation Challenge
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- title: rtm_emulation
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- emoji: 🤖
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- colorFrom: gray
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- colorTo: green
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- sdk: static
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- sdk_version: "latest"
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- pinned: false
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  ---
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- Last update: 30-06-2025
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  <img src="https://elias-ai.eu/wp-content/uploads/2023/09/elias_logo_big-1.png" alt="elias_logo" style="width:15%; display: inline-block; margin-right: 150px;">
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  <img src="https://elias-ai.eu/wp-content/uploads/2024/01/EN_FundedbytheEU_RGB_WHITE-Outline-1.png" alt="eu_logo" style="width:20%; display: inline-block;">
@@ -46,15 +39,7 @@ Last update: 30-06-2025
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  | **Model** | **MRE A1 (%)** | **MRE A2 (%)** | **MRE B1 (%)** | **MRE B2 (%)** | **Score** | **Runtime** | **Rank** |
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  |-----------|---------------|---------------|---------------|---------------|----------|----------|--------|
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- | Jasdeep_Emulator_3 | 0.090 | 3.117 | 0.566 | 6.108 | 1.525 | 89.359 | 1° |
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- | Hugo2 | 0.144 | 2.868 | 0.610 | 5.033 | 2.300 | 5.382 | 2° |
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- | rpnn1 | 0.133 | 5.883 | 0.583 | 5.561 | 2.525 | 19.082 | 3° |
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- | rpgprv2 | 0.176 | 3.835 | 0.640 | 7.050 | 4.000 | 35.650 | 4° |
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- | Jasdeep_Emulator_2 | 0.886 | 3.895 | 0.768 | 6.176 | 5.625 | 2.078 | 5° |
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- | Krtek | 0.545 | 7.693 | 0.823 | 7.877 | 6.500 | 0.764 | 6° |
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- | rpcvae | 0.185 | 11.996 | 0.918 | 15.313 | 6.700 | 0.546 | 7° |
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- | Jobaman1 | 0.296 | 10.093 | | 23.258 | 7.675 | 6.150 | 8° |
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- | baseline | 0.998 | 12.604 | 1.084 | 7.072 | 8.150 | 0.241 | 9° |
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  ## **Introduction**
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@@ -240,8 +225,9 @@ All evaluation scripts will be publicly available on GitLab and Huggingface to e
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  Note that only the **`LUTdata`** matrix (i.e., the predictions) are needed. A baseline example of this file is available for participants (`baseline_Sn.h5`).
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  We encourage participants to compress their hdf5 files using the deflate option.
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- - Each prediction file must be stored in the `results` folder in this repository. The prediction files should be named using the emulator/model name followed by
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- the scenario-track ID (e.g. `/results/mymodel_A1.h5`). A global attributed named `runtime` must be included to report the
 
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  computational efficiency of your model (value expressed in seconds).
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  Note that all predictions for different scenario-tracks should be stored in separate files.
247
 
 
8
  - atmosphere radiative transfer models
9
  - hyperspectral
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  pretty_name: Atmospheric Radiative Transfer Emulation Challenge
 
 
 
 
 
 
 
11
  ---
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+ Last update: 08-05-2025
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  <img src="https://elias-ai.eu/wp-content/uploads/2023/09/elias_logo_big-1.png" alt="elias_logo" style="width:15%; display: inline-block; margin-right: 150px;">
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  <img src="https://elias-ai.eu/wp-content/uploads/2024/01/EN_FundedbytheEU_RGB_WHITE-Outline-1.png" alt="eu_logo" style="width:20%; display: inline-block;">
 
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  | **Model** | **MRE A1 (%)** | **MRE A2 (%)** | **MRE B1 (%)** | **MRE B2 (%)** | **Score** | **Runtime** | **Rank** |
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  |-----------|---------------|---------------|---------------|---------------|----------|----------|--------|
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+ | baseline | 0.998 | 12.604 | 1.065 | 7.072 | 1.000 | 2.400 | 1° |
 
 
 
 
 
 
 
 
43
 
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  ## **Introduction**
45
 
 
225
  Note that only the **`LUTdata`** matrix (i.e., the predictions) are needed. A baseline example of this file is available for participants (`baseline_Sn.h5`).
226
  We encourage participants to compress their hdf5 files using the deflate option.
227
 
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+ - Each prediction file must be stored in`predictions` subfolder within the corresponding
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+ scenario folder (e.g., (e.g. `/scenarioA/predictions`). The prediction files should be named using the emulator/model name followed by the scenario-track ID
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+ (e.g. `/scenarioA/predictions/mymodel_A1.h5`). A global attributed named `runtime`must be included to report the
231
  computational efficiency of your model (value expressed in seconds).
232
  Note that all predictions for different scenario-tracks should be stored in separate files.
233
 
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- {
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- "name": "FiLM-Conditioned Emulator",
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- "authors": ["Jose Marie Antonio Minoza"],
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- "affiliations": ["Center for AI Research PH"],
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- "description": "Feature-wise Linear Modulation (FiLM)-conditioned model with parameter unification",
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- "url": "",
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- "email": "jomaminoza.acads@gmail.com"
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+ "description": "One GP emulator per transfer function, with gaussian kernel and 10 PCA",
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+ "url": "",
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+ "doi": "https://doi.org/10.1109/TGRS.2021.3071376",
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+ "email": "jorge.vicent@uv.es"
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- "description": "2nd order hypersurface polynomial fitting",
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- "url": "",
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- "doi": ""
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