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Found 6 papers, 1 papers with code
LERENet: Eliminating Intra-class Differences for Metal Surface Defect Few-shot Semantic Segmentation
Since the relation structure of local features embedded in graph space will help to eliminate \textit{Semantic Difference}, we employ Multi-Prototype Reasoning (MPR) module, extracting local descriptors based prototypes and analyzing local-view feature relevance in support-query pairs.
Deep Bayesian Reinforcement Learning for Spacecraft Proximity Maneuvers and Docking
This innovative approach allows the state-value function to be expressed as a Lyapunov function, leveraging the Gaussian process and deep kernel learning.
Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation
Unlike existing diffusion models that train neural networks to learn the score function, we develop a training-free score estimation method.
Contrastive Prompt Learning-based Code Search based on Interaction Matrix
However, existing code search methods still suffer from two performance constraints: inadequate semantic representation and the semantic gap between natural language (NL) and programming language (PL).
Seeking the Yield Barrier: High-Dimensional SRAM Evaluation Through Optimal Manifold
We then generalize it with infinite components and derive the novel optimal manifold concept, which bridges the surrogate-based and importance sampling (IS) yield estimation methods.
A Multilayer Framework for Online Metric Learning
Furthermore, in a progressively and nonlinearly learning way, MLOML has a stronger learning ability than traditional online metric learning in the case of limited available training data.
