8 citations · 12 across the 5 of their papers we have counts for
3 papers · 1 filter
Score-based Outlier Generation via Controlling the Radon-Nikodym Derivative
Amartya Mukherjee, Tristan Milne, Kry Yik-Chau Lui +2
Outliers are important for stress-testing algorithms and understanding system behaviour under rare conditions. Despite being commonly described as low-likelihood events, existing g…
Trust the Critics: Generatorless and Multipurpose WGANs with Initial Convergence Guarantees
Tristan Milne, Étienne Bilocq, Adrian Nachman
Inspired by ideas from optimal transport theory we present Trust the Critics (TTC), a new algorithm for generative modelling. This algorithm eliminates the trainable generator from…
Wasserstein GANs with Gradient Penalty Compute Congested Transport
Tristan Milne, Adrian Nachman
Wasserstein GANs with Gradient Penalty (WGAN-GP) are a very popular method for training generative models to produce high quality synthetic data. While WGAN-GP were initially devel…