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Found 6 papers, 1 papers with code
Traffic Prediction Based on Random Connectivity in Deep Learning with Long Short-Term Memory
So, the RCLSTM, with certain intrinsic sparsity, have many neural connections absent (distinguished from the full connectivity) and which leads to the reduction of the parameters to be trained and the computational cost.
Deep Learning with Long Short-Term Memory for Time Series Prediction
Time series prediction can be generalized as a process that extracts useful information from historical records and then determines future values.
Kullback-Leibler Divergence-Based Out-of-Distribution Detection with Flow-Based Generative Models
For point-wise anomaly detection, our method achieves 90. 7\% AUROC on average and outperforms the baseline by 5. 2\% AUROC.
Learning Safe Neural Network Controllers with Barrier Certificates
We provide a novel approach to synthesize controllers for nonlinear continuous dynamical systems with control against safety properties.
RelationRS: Relationship Representation Network for Object Detection in Aerial Images
To address these issues, we propose a relationship representation network for object detection in aerial images (RelationRS): 1) Firstly, multi-scale features are fused and enhanced by a dual relationship module (DRM) with conditional convolution.
Uncertainty-driven and Adversarial Calibration Learning for Epicardial Adipose Tissue Segmentation
we propose a novel feature latent space multilevel supervision network (SPDNet) with uncertainty-driven and adversarial calibration learning to enhance segmentation for more accurate EAT volume estimation.
