Machine learning models are susceptible to a variety of attacks that can...
We systematically study a wide variety of image-based generative models
...
Likelihood-based deep generative models have recently been shown to exhi...
In the traditional federated learning setting, a central server coordina...
Deep learning has had tremendous success at learning low-dimensional
rep...
Natural data observed in ℝ^n is often constrained to an
m-dimensional ma...
As machine learning becomes more widespread throughout society, aspects
...
Likelihood-based, or explicit, deep generative models use neural network...
Normalizing flows are generative models that provide tractable density
e...
Multi-goal reaching is an important problem in reinforcement learning ne...