3 citations · 4 across the 3 of their papers we have counts for
4 papers
Adaptive recurrent vision performs zero-shot computation scaling to unseen difficulty levels
Vijay Veerabadran, Srinivas Ravishankar, Yuan Tang +2
Humans solving algorithmic (or) reasoning problems typically exhibit solution times that grow as a function of problem difficulty. Adaptive recurrent neural networks have been show…
Learning compact generalizable neural representations supporting perceptual grouping
Vijay Veerabadran, Virginia R. de Sa
Work at the intersection of vision science and deep learning is starting to explore the efficacy of deep convolutional networks (DCNs) and recurrent networks in solving perceptual…
Adversarial Distortion for Learned Video Compression
Vijay Veerabadran, Reza Pourreza, Amirhossein Habibian +1
In this paper, we present a novel adversarial lossy video compression model. At extremely low bit-rates, standard video coding schemes suffer from unpleasant reconstruction artifac…
Learning long-range spatial dependencies with horizontal gated-recurrent units
Drew Linsley, Junkyung Kim, Vijay Veerabadran +1
Progress in deep learning has spawned great successes in many engineering applications. As a prime example, convolutional neural networks, a type of feedforward neural networks, ar…