38 citations · 42 across the 3 of their papers we have counts for
6 papers
Prediction-Oriented Bayesian Active Learning
Freddie Bickford Smith, Andreas Kirsch, Sebastian Farquhar +3
Information-theoretic approaches to active learning have traditionally focused on maximising the information gathered about the model parameters, most commonly by optimising the BA…
Does "Deep Learning on a Data Diet" reproduce? Overall yes, but GraNd at Initialization does not
Andreas Kirsch
The paper 'Deep Learning on a Data Diet' by Paul et al. (2021) introduces two innovative metrics for pruning datasets during the training of neural networks. While we are able to r…
Speeding Up BatchBALD: A k-BALD Family of Approximations for Active Learning
Andreas Kirsch
Active learning is a powerful method for training machine learning models with limited labeled data. One commonly used technique for active learning is BatchBALD, which uses Bayesi…
Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities
Andreas Kirsch, Yarin Gal
Recently proposed methods in data subset selection, that is active learning and active sampling, use Fisher information, Hessians, similarity matrices based on gradients, and gradi…
Plex: Towards Reliability using Pretrained Large Model Extensions
Dustin Tran, Jeremiah Liu, Michael W. Dusenberry +23
A recent trend in artificial intelligence is the use of pretrained models for language and vision tasks, which have achieved extraordinary performance but also puzzling failures. P…
Corrigendum to "Inverse Problems for abstract evolution equations II: higher order differentiability for viscoelasticity
Andreas Kirsch, Andreas Rieder
In our paper [SIAM J.\ Appl.~Math.\ 79-6 (2019), https://doi.org/10.1137/19M1269403] we considered full waveform inversion (FWI) in the viscoelastic regime. FWI entails the nonline…