109 citations · 522 across the 51 of their papers we have counts for
3 papers · 1 filter
EuclidNets: An Alternative Operation for Efficient Inference of Deep Learning Models
Xinlin Li, Mariana Parazeres, Adam Oberman +3
With the advent of deep learning application on edge devices, researchers actively try to optimize their deployments on low-power and restricted memory devices. There are establish…
Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Models
Vikram Voleti, Christopher Pal, Adam Oberman
Generative models based on denoising diffusion techniques have led to an unprecedented increase in the quality and diversity of imagery that is now possible to create with neural g…
On the Generalization of Representations in Reinforcement Learning
Charline Le Lan, Stephen Tu, Adam Oberman +2
In reinforcement learning, state representations are used to tractably deal with large problem spaces. State representations serve both to approximate the value function with few p…