SimTech EXC 2075 Project Network 6 "Machine learning for simulation"
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461 to 470 of 867 Results
simulate_data_and_pmps.Rd
May 25, 2023 - Replication Code for: Meta-Uncertainty in Bayesian Model Comparison
Unknown - 679 B - MD5: fc357468fc11d54cabff4439a3fc4839
simulate_data_bayesian_linear_regression.Rd
May 25, 2023 - Replication Code for: Meta-Uncertainty in Bayesian Model Comparison
Unknown - 512 B - MD5: 18788fbf4268c67c6b8a0693ad791bb3
SIR.Rd
May 25, 2023 - Replication Code for: Meta-Uncertainty in Bayesian Model Comparison
Unknown - 524 B - MD5: e746eb30a13ba4ab677762a898d06bc2
sir_simulator.R
May 25, 2023 - Replication Code for: Meta-Uncertainty in Bayesian Model Comparison
R Syntax - 801 B - MD5: 62d960b88fb577d9128a6d90e9d0092e
test-log_sum_exp.R
May 25, 2023 - Replication Code for: Meta-Uncertainty in Bayesian Model Comparison
R Syntax - 117 B - MD5: 2b0519a5f7be7f5bf1d6fb09d4f6aeb7
testthat.R
May 25, 2023 - Replication Code for: Meta-Uncertainty in Bayesian Model Comparison
R Syntax - 84 B - MD5: c9e4897898f5627111b8ce12e5f4daaf
Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]
Apr 5, 2023
Holzmüller, David; Zaverkin, Viktor; Kästner, Johannes; Steinwart, Ingo, 2023, "Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]", https://doi.org/10.18419/DARUS-3394, DaRUS, V1
This dataset contains code and data for the third arXiv version of our paper "A Framework and Benchmark for Deep Batch Active Learning for Regression". The code can be used to reproduce the results, to benchmark new methods, or to apply the presented methods to new Deep Batch Active Learning problems. The code is also available on GitHub. Informati...
algorithms.py
Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]
Python Source Code - 26.9 KB - MD5: 8992d130a29ce591cf770f831365e711
analysis.py
Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]
Python Source Code - 24.0 KB - MD5: e7e55610a01b7baf79167d03185187bb
benchmark.ipynb
Apr 5, 2023 - Code and Data for: A Framework and Benchmark for Deep Batch Active Learning for Regression [arXiv v3]
Jupyter Notebook - 116.3 KB - MD5: b64ba74944c8c63b6cdbcb5c3f3c3ca5
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