5 papers · 1 filter
Uncertainty Estimation in Autoregressive Structured Prediction
Andrey Malinin, Mark Gales
Uncertainty estimation is important for ensuring safety and robustness of AI systems. While most research in the area has focused on un-structured prediction tasks, limited work ha…
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness
Andrey Malinin, Mark Gales
Ensemble approaches for uncertainty estimation have recently been applied to the tasks of misclassification detection, out-of-distribution input detection and adversarial attack de…
Ensemble Distribution Distillation
Andrey Malinin, Bruno Mlodozeniec, Mark Gales
Ensembles of models often yield improvements in system performance. These ensemble approaches have also been empirically shown to yield robust measures of uncertainty, and are capa…
Prior Networks for Detection of Adversarial Attacks
Andrey Malinin, Mark Gales
Adversarial examples are considered a serious issue for safety critical applications of AI, such as finance, autonomous vehicle control and medicinal applications. Though significa…
Predictive Uncertainty Estimation via Prior Networks
Andrey Malinin, Mark Gales
Estimating how uncertain an AI system is in its predictions is important to improve the safety of such systems. Uncertainty in predictive can result from uncertainty in model param…