471 citations · 3.4k across the 65 of their papers we have counts for
65 papers
Studying Large Language Model Generalization with Influence Functions
Roger Grosse, Juhan Bae, Cem Anil +14
When trying to gain better visibility into a machine learning model in order to understand and mitigate the associated risks, a potentially valuable source of evidence is: which tr…
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds
Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi +3
Mutual information (MI) is a fundamental quantity in information theory and machine learning. However, direct estimation of MI is intractable, even if the true joint probability de…
Efficient Parametric Approximations of Neural Network Function Space Distance
Nikita Dhawan, Sicong Huang, Juhan Bae +1
It is often useful to compactly summarize important properties of model parameters and training data so that they can be used later without storing and/or iterating over the entire…
On Implicit Bias in Overparameterized Bilevel Optimization
Paul Vicol, Jonathan Lorraine, Fabian Pedregosa +2
Many problems in machine learning involve bilevel optimization (BLO), including hyperparameter optimization, meta-learning, and dataset distillation. Bilevel problems consist of tw…
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve
Juhan Bae, Michael R. Zhang, Michael Ruan +4
Variational autoencoders (VAEs) are powerful tools for learning latent representations of data used in a wide range of applications. In practice, VAEs usually require multiple trai…
Path Independent Equilibrium Models Can Better Exploit Test-Time Computation
Cem Anil, Ashwini Pokle, Kaiqu Liang +5
Designing networks capable of attaining better performance with an increased inference budget is important to facilitate generalization to harder problem instances. Recent efforts…