activity
20172023
most citedLanguage Generation with Recurrent Generative Adversarial Networks without Pre-training

90 citations · 298 across the 31 of their papers we have counts for

collaborators
Showing cs.LGShow all

22 papers · 1 filter

cs.LG20232 cited

Diverse and Aligned Audio-to-Video Generation via Text-to-Video Model Adaptation

Guy Yariv, Itai Gat, Sagie Benaim +3

We consider the task of generating diverse and realistic videos guided by natural audio samples from a wide variety of semantic classes. For this task, the videos are required to b…

cs.LG2023

Centered Self-Attention Layers

Ameen Ali, Tomer Galanti, Lior Wolf

The self-attention mechanism in transformers and the message-passing mechanism in graph neural networks are repeatedly applied within deep learning architectures. We show that this…

cs.LG2022

On Disentangled and Locally Fair Representations

Yaron Gurovich, Sagie Benaim, Lior Wolf

We study the problem of performing classification in a manner that is fair for sensitive groups, such as race and gender. This problem is tackled through the lens of disentangled a…

cs.LG2022

Dynamically-Scaled Deep Canonical Correlation Analysis

Tomer Friedlander, Lior Wolf

Canonical Correlation Analysis (CCA) is a method for feature extraction of two views by finding maximally correlated linear projections of them. Several variants of CCA have been i…

cs.LG2021

Mixing between the Cross Entropy and the Expectation Loss Terms

Barak Battash, Lior Wolf, Tamir Hazan

The cross entropy loss is widely used due to its effectiveness and solid theoretical grounding. However, as training progresses, the loss tends to focus on hard to classify samples…

cs.LG2021

In Defense of the Learning Without Forgetting for Task Incremental Learning

Guy Oren, Lior Wolf

Catastrophic forgetting is one of the major challenges on the road for continual learning systems, which are presented with an on-line stream of tasks. The field has attracted cons…