Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...
Abstract: The leaf area index (LAI) is a biophysical variable related to atmosphere-biosphere exchange of CO 2. One way to obtain LAI value is by the Moderate Resolution Imaging Spectroradiometer ...
Abstract: In this paper, we investigate the cooperative modulation classification problem under multipath scenarios with blind channel information. Multipath channels cause severe degradation on the ...
Quantum computing news usually picks up near the end of the year, as companies try to provide evidence that they are hitting benchmarks on time. However, there have been interesting announcements as ...
This digital series—featuring scholars from CSIS Futures Lab and AI evaluation experts from Scale AI—explores how large language models approach critical foreign policy decision-making scenarios. This ...
Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
Create a hybrid pricing model using the ICE model and traditional valuation Conclusion: A 'hybrid pricing model' that integrates the ICE model (expected value/attractiveness) and traditional valuation ...
A faster variant running a single density greedy yields a $1/2$ approximation (Algorithm 7). For the non-monotone case, the algorithm adopts the "density greedy + random deletion with fixed ...
Expectation-Maximization (EM) algorithm is used to find the gene expression values that maximize the likelihood function. Recovering multi-gene reads via MLE-EM model was previously used to quantify ...
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