activity
20192021
most citedDeep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case

353 citations · 353 across the 1 of their papers we have counts for

collaborators

6 papers

cs.CV2021

Joint Representation Learning and Novel Category Discovery on Single- and Multi-modal Data

Xuhui Jia, Kai Han, Yukun Zhu +1

This paper studies the problem of novel category discovery on single- and multi-modal data with labels from different but relevant categories. We present a generic, end-to-end fram…

cs.CV2020

Contrastive Learning for Label-Efficient Semantic Segmentation

Xiangyun Zhao, Raviteja Vemulapalli, Philip Mansfield +4

Collecting labeled data for the task of semantic segmentation is expensive and time-consuming, as it requires dense pixel-level annotations. While recent Convolutional Neural Netwo…

cs.CV2020

Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze

Bardia Doosti, Ching-Hui Chen, Raviteja Vemulapalli +3

Mutual gaze detection, i.e., predicting whether or not two people are looking at each other, plays an important role in understanding human interactions. In this work, we focus on…

cs.CV2020

Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation

Huiyu Wang, Yukun Zhu, Bradley Green +3

Convolution exploits locality for efficiency at a cost of missing long range context. Self-attention has been adopted to augment CNNs with non-local interactions. Recent works prov…

cs.LG2020353 cited

Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case

Neo Wu, Bradley Green, Xue Ben +1

In this paper, we present a new approach to time series forecasting. Time series data are prevalent in many scientific and engineering disciplines. Time series forecasting is a cru…

cs.CV2019

Search to Distill: Pearls are Everywhere but not the Eyes

Yu Liu, Xuhui Jia, Mingxing Tan +4

Standard Knowledge Distillation (KD) approaches distill the knowledge of a cumbersome teacher model into the parameters of a student model with a pre-defined architecture. However,…