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Found 7 papers, 1 papers with code
DGoT: Dynamic Graph of Thoughts for Scientific Abstract Generation
However, due to the hallucination problem of LLM, it is often necessary to improve the reliability of the results through multi-round query prompt approach such as Graph of Thoughts (GoT), which also brings additional reasoning costs.
KDSM: An uplift modeling framework based on knowledge distillation and sample matching
The teacher model is the uplift decision tree (UpliftDT), whose structure is exploited to construct counterfactual sample pairs, and the pairwise incremental prediction is treated as another objective for the student model.
A Lightweight Dual-Domain Attention Framework for Sparse-View CT Reconstruction
After the restored Radon data is reconstructed to an image, the image is sent into the second CAGAN trained for recovering the details, so that a high-quality image is obtained.
Robust Data-Driven Linear Power Flow Model with Probability Constrained Worst-Case Errors
To limit the probability of unacceptable worst-case linearization errors that might yield risks for power system operations, this letter proposes a robust data-driven linear power flow (RD-LPF) model.
A Physics-based and Data-driven Linear Three-Phase Power Flow Model for Distribution Power Systems
Case studies have demonstrated that our model generally has 2 to over 10-fold smaller average errors than other linear power flow models, enjoys a satisfying accuracy against bad data, and facilitates a faster solution to DPS analysis and optimization problems.
A Lightweight Structure Aimed to Utilize Spatial Correlation for Sparse-View CT Reconstruction
Sparse-view computed tomography (CT) is known as a widely used approach to reduce radiation dose while accelerating imaging through lowered projection views and correlated calculations.
Real-Time Limited-View CT Inpainting and Reconstruction with Dual Domain Based on Spatial Information
In stage one, to better utilize prior information in the Radon domain, we design an adversarial autoencoder to complement the Radon data.
