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Found 6 papers, 2 papers with code
A Survey of Neural Network Robustness Assessment in Image Recognition
We investigate the perturbation metrics and range representations used to measure the degree of perturbations on images, as well as the robustness metrics specifically for the robustness conditions of classification models.
A 5' UTR Language Model for Decoding Untranslated Regions of mRNA and Function Predictions
The model outperformed the best-known benchmark by up to 42% for predicting the Mean Ribosome Loading, and by up to 60% for predicting the Translation Efficiency and the mRNA Expression Level.
An Underwater Image Semantic Segmentation Method Focusing on Boundaries and a Real Underwater Scene Semantic Segmentation Dataset
Based on this dataset, we propose a semi-supervised underwater semantic segmentation network focusing on the boundaries(US-Net: Underwater Segmentation Network).
Decoupled Data Based Approach for Learning to Control Nonlinear Dynamical Systems
This paper proposes a novel decoupled data-based control (D2C) algorithm that addresses this problem using a decoupled, `open loop - closed loop', approach.
A Separation-Based Design to Data-Driven Control for Large-Scale Partially Observed Systems
This paper studies the partially observed stochastic optimal control problem for systems with state dynamics governed by Partial Differential Equations (PDEs) that leads to an extremely large problem.
Stochastic Feedback Control of Systems with Unknown Nonlinear Dynamics
This paper studies the stochastic optimal control problem for systems with unknown dynamics.
