Search Results for author:
Found 4 papers, 2 papers with code
Visual Imitation Learning with Calibrated Contrastive Representation
Adversarial Imitation Learning (AIL) allows the agent to reproduce expert behavior with low-dimensional states and actions.
A Benchmark Study on Calibration
As far as we are aware, our research represents the first large-scale investigation into calibration properties and the premier study of calibration issues within NAS.
Dual Focal Loss for Calibration
While different variants of focal loss have been explored, it is difficult to find a balance between over-confidence and under-confidence.
Calibrating a Deep Neural Network with Its Predecessors
However, early stopping, as a well-known technique to mitigate overfitting, fails to calibrate networks.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
