activity
20192022
most citedCapsule Networks with Max-Min Normalization

40 citations · 52 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR20221 cited

MP2: A Momentum Contrast Approach for Recommendation with Pointwise and Pairwise Learning

Menghan Wang, Yuchen Guo, Zhenqi Zhao +4

Binary pointwise labels (aka implicit feedback) are heavily leveraged by deep learning based recommendation algorithms nowadays. In this paper we discuss the limited expressiveness…

cs.CV20201 cited

Bi-Dimensional Feature Alignment for Cross-Domain Object Detection

Zhen Zhao, Yuhong Guo, Jieping Ye

Recently the problem of cross-domain object detection has started drawing attention in the computer vision community. In this paper, we propose a novel unsupervised cross-domain de…

cs.CV20201 cited

Ensemble Model with Batch Spectral Regularization and Data Blending for Cross-Domain Few-Shot Learning with Unlabeled Data

Zhen Zhao, Bingyu Liu, Yuhong Guo +1

In this paper, we present our proposed ensemble model with batch spectral regularization and data blending mechanisms for the Track 2 problem of the cross-domain few-shot learning…

cs.CV20199 cited

Fast Inference in Capsule Networks Using Accumulated Routing Coefficients

Zhen Zhao, Ashley Kleinhans, Gursharan Sandhu +2

We present a method for fast inference in Capsule Networks (CapsNets) by taking advantage of a key insight regarding the routing coefficients that link capsules between adjacent ne…

cs.CV201940 cited

Capsule Networks with Max-Min Normalization

Zhen Zhao, Ashley Kleinhans, Gursharan Sandhu +2

Capsule Networks (CapsNet) use the Softmax function to convert the logits of the routing coefficients into a set of normalized values that signify the assignment probabilities betw…