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Found 7 papers, 0 papers with code
Stochastic Dynamic Power Dispatch with High Generalization and Few-Shot Adaption via Contextual Meta Graph Reinforcement Learning
To fill these gaps, a novel contextual meta graph reinforcement learning (Meta-GRL) for a highly generalized multi-stage optimal dispatch policy is proposed.
Exploration of Adolescent Depression Risk Prediction Based on Census Surveys and General Life Issues
We introduced a method for managing severely imbalanced high-dimensional data and an adaptive predictive approach tailored to data structure characteristics.
Computing the Bounds of the Number of Reticulations in a Tree-Child Network That Displays a Set of Trees
Phylogenetic network is an evolutionary model that uses a rooted directed acyclic graph (instead of a tree) to model an evolutionary history of species in which reticulate events (e. g., hybrid speciation or horizontal gene transfer) occurred.
Ignorance Is Bliss: The Screening Effect of (Noisy) Information
While more precise information allows the firm to make ex-post more efficient investment decisions, noisier information has an ex-ante screening effect that allows the firm to attract on-average better managers.
A Fast and Scalable Method for Inferring Phylogenetic Networks from Trees by Aligning Lineage Taxon Strings
The reconstruction of phylogenetic networks is an important but challenging problem in phylogenetics and genome evolution, as the space of phylogenetic networks is vast and cannot be sampled well.
Can Multiple Phylogenetic Trees Be Displayed in a Tree-Child Network Simultaneously?
It is also proved that any set of multiple binary phylogenetic trees can always simultaneously be displayed in some non-binary tree-child network on the same taxa set, where each nonleaf node is of either indegree one and outdegree two or indegree at least two and outdegree out.
Learning and Inference on Generative Adversarial Quantum Circuits
Quantum mechanics is inherently probabilistic in light of Born's rule.
