6.7k citations · 6.8k across the 7 of their papers we have counts for
10 papers
Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation
Martin Bertran, Walter Talbott, Nitish Srivastava +1
Learning generalizeable policies from visual input in the presence of visual distractions is a challenging problem in reinforcement learning. Recently, there has been renewed inter…
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning
Yue Wu, Shuangfei Zhai, Nitish Srivastava +4
Offline Reinforcement Learning promises to learn effective policies from previously-collected, static datasets without the need for exploration. However, existing Q-learning and ac…
An Attention Free Transformer
Shuangfei Zhai, Walter Talbott, Nitish Srivastava +4
We introduce Attention Free Transformer (AFT), an efficient variant of Transformers that eliminates the need for dot product self attention. In an AFT layer, the key and value are…
Unconstrained Scene Generation with Locally Conditioned Radiance Fields
Terrance DeVries, Miguel Angel Bautista, Nitish Srivastava +2
We tackle the challenge of learning a distribution over complex, realistic, indoor scenes. In this paper, we introduce Generative Scene Networks (GSN), which learns to decompose sc…
On the generalization of learning-based 3D reconstruction
Miguel Angel Bautista, Walter Talbott, Shuangfei Zhai +2
State-of-the-art learning-based monocular 3D reconstruction methods learn priors over object categories on the training set, and as a result struggle to achieve reasonable generali…
Capsules with Inverted Dot-Product Attention Routing
Yao-Hung Hubert Tsai, Nitish Srivastava, Hanlin Goh +1
We introduce a new routing algorithm for capsule networks, in which a child capsule is routed to a parent based only on agreement between the parent's state and the child's vote. T…