289 citations · 395 across the 10 of their papers we have counts for
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stat.ML2022★ 1 cited
On the Nash equilibrium of moment-matching GANs for stationary Gaussian processes
Sixin Zhang
Generative Adversarial Networks (GANs) learn an implicit generative model from data samples through a two-player game. In this paper, we study the existence of Nash equilibrium of…
stat.ML2020★ 1 cited
Particle gradient descent model for point process generation
Antoine Brochard, Bartłomiej Błaszczyszyn, Stéphane Mallat +1
This paper presents a statistical model for stationary ergodic point processes, estimated from a single realization observed in a square window. With existing approaches in stochas…
stat.ML2012★ 289 cited
No More Pesky Learning Rates
Tom Schaul, Sixin Zhang, Yann LeCun
The performance of stochastic gradient descent (SGD) depends critically on how learning rates are tuned and decreased over time. We propose a method to automatically adjust multipl…