Search Results for author:
Found 5 papers, 4 papers with code
Calibrated Perception Uncertainty Across Objects and Regions in Bird's-Eye-View
In driving scenarios with poor visibility or occlusions, it is important that the autonomous vehicle would take into account all the uncertainties when making driving decisions, including choice of a safe speed.
On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers
This motivates the fit-on-the-test view on evaluation: first, approximate a calibration map on the test data, and second, quantify its distance from the identity.
Correlated daily time series and forecasting in the M4 competition
We participated in the M4 competition for time series forecasting and describe here our methods for forecasting daily time series.
Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration
Class probabilities predicted by most multiclass classifiers are uncalibrated, often tending towards over-confidence.
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration
Class probabilities predicted by most multiclass classifiers are uncalibrated, often tending towards over-confidence.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
