5 citations · 9 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 4 cited
Grounding Representation Similarity with Statistical Testing
Frances Ding, Jean-Stanislas Denain, Jacob Steinhardt
To understand neural network behavior, recent works quantitatively compare different networks' learned representations using canonical correlation analysis (CCA), centered kernel a…
stat.ML2020★ 5 cited
MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference
Achille Thin, Nikita Kotelevskii, Jean-Stanislas Denain +4
In this contribution, we propose a new computationally efficient method to combine Variational Inference (VI) with Markov Chain Monte Carlo (MCMC). This approach can be used with g…