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Found 4 papers, 3 papers with code
On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design
The gradient information is often needed for efficient EIG optimization, and as a result the ability to estimate the gradient of EIG is essential for BED problems.
Skill requirements in job advertisements: A comparison of skill-categorization methods based on explanatory power in wage regressions
In this paper, we compare different methods to extract skill requirements from job advertisements.
Is decentralized finance actually decentralized? A social network analysis of the Aave protocol on the Ethereum blockchain
Our research pioneers a blockchain network study that applies social network analysis to measure the level, dynamics, and impacts of decentralization in DeFi token transactions on the Ethereum blockchain.
An approximate KLD based experimental design for models with intractable likelihoods
Data collection is a critical step in statistical inference and data science, and the goal of statistical experimental design (ED) is to find the data collection setup that can provide most information for the inference.
