research
∙
08/25/2023
Fine-tuning can cripple your foundation model; preserving features may be the solution
Pre-trained foundation models, owing primarily to their enormous capacit...
share
research
∙
09/24/2022
Raising the Bar on the Evaluation of Out-of-Distribution Detection
In image classification, a lot of development has happened in detecting ...
research
∙
10/29/2021
Deep Deterministic Uncertainty for Semantic Segmentation
We extend Deep Deterministic Uncertainty (DDU), a method for uncertainty...
research
∙
02/23/2021
Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty
We show that a single softmax neural net with minimal changes can beat t...
research
∙
12/24/2020
On Batch Normalisation for Approximate Bayesian Inference
We study batch normalisation in the context of variational inference met...
research
∙
02/21/2020
Calibrating Deep Neural Networks using Focal Loss
Miscalibration – a mismatch between a model's confidence and its correct...
research
∙
06/20/2019
Let's Take This Online: Adapting Scene Coordinate Regression Network Predictions for Online RGB-D Camera Relocalisation
Many applications require a camera to be relocalised online, without exp...
research
∙
11/30/2018
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation
Deep learning has been revolutionary for computer vision and semantic se...
research
∙
11/23/2018
