- 15 Jun, 2020 1 commit
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feichtinger authored
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- 10 Jun, 2020 2 commits
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feichtinger authored
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feichtinger authored
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- 04 Jun, 2020 1 commit
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feichtinger authored
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- 29 May, 2020 1 commit
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feichtinger authored
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- 20 May, 2020 1 commit
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feichtinger authored
added some comments and cleaned a bit
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- 19 May, 2020 3 commits
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feichtinger authored
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feichtinger authored
introduced colored scatter plots for finding this.
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feichtinger authored
Doing this as I am preparing for the meeting tomorrow. I want to restructure and clarify a bit, so that I directly can use the notebook during my presentation.
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- 23 Mar, 2020 1 commit
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feichtinger authored
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- 20 Mar, 2020 1 commit
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feichtinger authored
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- 24 Feb, 2020 1 commit
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feichtinger authored
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- 14 Feb, 2020 1 commit
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feichtinger authored
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- 06 Feb, 2020 2 commits
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feichtinger authored
Each file contains points which cover a very small part of the parameter space. It's more like having only one averaged measurement per file. If the fitting is allowed to include points from all file, the fit is trivially good, since the variation of parameters per file is minimal. Leaving files out in training leads to miserable fits for the unseen data.
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feichtinger authored
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- 05 Feb, 2020 1 commit
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feichtinger authored
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- 28 Jan, 2020 1 commit
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feichtinger authored
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- 20 Jan, 2020 2 commits
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feichtinger authored
swissfel-modelA-df_1.csv using - Model: build_ff_mdl_smallA params = { 'mult_neuron': [1, 2, 4], 'activation': ['relu', 'elu', 'tanh'], 'batch_size': [10, 25, 50, 100], 'noise': [0.1, 0.01, 0.001] }
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feichtinger authored
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- 16 Jan, 2020 1 commit
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adelmann authored
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- 15 Jan, 2020 3 commits
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snuverink_j authored
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snuverink_j authored
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snuverink_j authored
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- 14 Jan, 2020 3 commits