104 citations · 673 across the 47 of their papers we have counts for
3 papers · 1 filter
Taming GANs with Lookahead-Minmax
Tatjana Chavdarova, Matteo Pagliardini, Sebastian U. Stich +2
Generative Adversarial Networks are notoriously challenging to train. The underlying minmax optimization is highly susceptible to the variance of the stochastic gradient and the ro…
Rethinking the Role of Gradient-Based Attribution Methods for Model Interpretability
Suraj Srinivas, Francois Fleuret
Current methods for the interpretability of discriminative deep neural networks commonly rely on the model's input-gradients, i.e., the gradients of the output logits w.r.t. the in…
Real-Time Segmentation Networks should be Latency Aware
Evann Courdier, Francois Fleuret
As scene segmentation systems reach visually accurate results, many recent papers focus on making these network architectures faster, smaller and more efficient. In particular, stu…