37 citations · 137 across the 20 of their papers we have counts for
9 papers · 1 filter
Alleviating Noisy Data in Image Captioning with Cooperative Distillation
Pierre Dognin, Igor Melnyk, Youssef Mroueh +4
Image captioning systems have made substantial progress, largely due to the availability of curated datasets like Microsoft COCO or Vizwiz that have accurate descriptions of their…
On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow
Youssef Mroueh, Truyen Nguyen
We consider the maximum mean discrepancy () GAN problem and propose a parametric kernelized gradient flow that mimics the min-max game in gradient regularized $\mathr…
Tabular Transformers for Modeling Multivariate Time Series
Inkit Padhi, Yair Schiff, Igor Melnyk +6
Tabular datasets are ubiquitous in data science applications. Given their importance, it seems natural to apply state-of-the-art deep learning algorithms in order to fully unlock t…
Unbalanced Sobolev Descent
Youssef Mroueh, Mattia Rigotti
We introduce Unbalanced Sobolev Descent (USD), a particle descent algorithm for transporting a high dimensional source distribution to a target distribution that does not necessari…
Active learning of deep surrogates for PDEs: Application to metasurface design
Raphaël Pestourie, Youssef Mroueh, Thanh V. Nguyen +2
Surrogate models for partial-differential equations are widely used in the design of meta-materials to rapidly evaluate the behavior of composable components. However, the training…
Kernel Stein Generative Modeling
Wei-Cheng Chang, Chun-Liang Li, Youssef Mroueh +1
We are interested in gradient-based Explicit Generative Modeling where samples can be derived from iterative gradient updates based on an estimate of the score function of the data…