5 citations · 6 across the 3 of their papers we have counts for
3 papers
A Framework for Large Scale Synthetic Graph Dataset Generation
Sajad Darabi, Piotr Bigaj, Dawid Majchrowski +3
Recently there has been increasing interest in developing and deploying deep graph learning algorithms for many tasks, such as fraud detection and recommender systems. Albeit, ther…
Tiered Pruning for Efficient Differentialble Inference-Aware Neural Architecture Search
Sławomir Kierat, Mateusz Sieniawski, Denys Fridman +4
We propose three novel pruning techniques to improve the cost and results of inference-aware Differentiable Neural Architecture Search (DNAS). First, we introduce Prunode, a stocha…
Pay Attention when Required
Swetha Mandava, Szymon Migacz, Alex Fit Florea
Transformer-based models consist of interleaved feed-forward blocks - that capture content meaning, and relatively more expensive self-attention blocks - that capture context meani…