3 citations · 8 across the 4 of their papers we have counts for
3 papers · 1 filter
A Geometric Framework for Understanding Memorization in Generative Models
Brendan Leigh Ross, Hamidreza Kamkari, Tongzi Wu +5
As deep generative models have progressed, recent work has shown them to be capable of memorizing and reproducing training datapoints when deployed. These findings call into questi…
Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks
Antoni Kowalczuk, Jan Dubiński, Atiyeh Ashari Ghomi +6
Large-scale vision models have become integral in many applications due to their unprecedented performance and versatility across downstream tasks. However, the robustness of these…
TabPFGen -- Tabular Data Generation with TabPFN
Junwei Ma, Apoorv Dankar, George Stein +2
Advances in deep generative modelling have not translated well to tabular data. We argue that this is caused by a mismatch in structure between popular generative models and discri…