Pruning neural networks at initialization would enable us to find sparse...
Uncertainty estimation is a key component in any deployed machine learni...
Estimating personalized treatment effects from high-dimensional observat...
We extend Deep Deterministic Uncertainty (DDU), a method for uncertainty...
ResNets constrained to be bi-Lipschitz, that is, approximately distance
...
We show that a single softmax neural net with minimal changes can beat t...
We propose a new model that estimates uncertainty in a single forward pa...
We introduce a method to speed up training by 2x and inference by 3x in ...
We propose a method for training a deterministic deep model that can fin...
We develop BatchBALD, a tractable approximation to the mutual informatio...
In large scale systems, approximate nearest neighbour search is a crucia...
Frame interpolation attempts to synthesise intermediate frames given one...
In this work we propose a simple unsupervised approach for next frame
pr...