1 citations · 1 across the 5 of their papers we have counts for
5 papers
AVQ-Attention: Adaptive Vector-Quantized Attention
Winfried van den dool, Patrick Forré, Amir Habibian +2
The complexity of attention over tokens remains a computational bottleneck in transformer models. Vector-Quantized (VQ) attention reduces this to $\mathcal{O…
Private PoEtry: Private In-Context Learning via Product of Experts
Rob Romijnders, Mohammad Mahdi Derakhshani, Jonathan Petit +3
In-context learning (ICL) enables Large Language Models (LLMs) to adapt to new tasks with only a small set of examples at inference time, thereby avoiding task-specific fine-tuning…
Adaptive Mesh-Quantization for Neural PDE Solvers
Winfried van den Dool, Maksim Zhdanov, Yuki M. Asano +1
Physical systems commonly exhibit spatially varying complexity, presenting a significant challenge for neural PDE solvers. While Graph Neural Networks can handle the irregular mesh…
DNA: Differentially private Neural Augmentation for contact tracing
Rob Romijnders, Christos Louizos, Yuki M. Asano +1
The COVID19 pandemic had enormous economic and societal consequences. Contact tracing is an effective way to reduce infection rates by detecting potential virus carriers early. How…
Protect Your Score: Contact Tracing With Differential Privacy Guarantees
Rob Romijnders, Christos Louizos, Yuki M. Asano +1
The pandemic in 2020 and 2021 had enormous economic and societal consequences, and studies show that contact tracing algorithms can be key in the early containment of the virus. Wh…