1.5k citations · 1.6k across the 5 of their papers we have counts for
6 papers
Integrating Categorical Semantics into Unsupervised Domain Translation
Samuel Lavoie, Faruk Ahmed, Aaron Courville
While unsupervised domain translation (UDT) has seen a lot of success recently, we argue that mediating its translation via categorical semantic features could broaden its applicab…
Detecting semantic anomalies
Faruk Ahmed, Aaron Courville
We critically appraise the recent interest in out-of-distribution (OOD) detection and question the practical relevance of existing benchmarks. While the currently prevalent trend i…
Improved Training of Wasserstein GANs
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky +2
Generative Adversarial Networks (GANs) are powerful generative models, but suffer from training instability. The recently proposed Wasserstein GAN (WGAN) makes progress toward stab…
PixelVAE: A Latent Variable Model for Natural Images
Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed +4
Natural image modeling is a landmark challenge of unsupervised learning. Variational Autoencoders (VAEs) learn a useful latent representation and model global structure well but ha…
Reducing Overfitting in Deep Networks by Decorrelating Representations
Michael Cogswell, Faruk Ahmed, Ross Girshick +2
One major challenge in training Deep Neural Networks is preventing overfitting. Many techniques such as data augmentation and novel regularizers such as Dropout have been proposed…
Candidate Constrained CRFs for Loss-Aware Structured Prediction
Faruk Ahmed, Daniel Tarlow, Dhruv Batra
When evaluating computer vision systems, we are often concerned with performance on a task-specific evaluation measure such as the Intersection-Over-Union score used in the PASCAL…