activity
20182023
most citedLearning Robust Global Representations by Penalizing Local Predictive Power

271 citations · 327 across the 18 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.LG2019★ 2 cited

Getting Topology and Point Cloud Generation to Mesh

Austin Dill, Chun-Liang Li, Songwei Ge +1

In this work, we explore the idea that effective generative models for point clouds under the autoencoding framework must acknowledge the relationship between a continuous surface,…

cs.IR2019

Personalizing Search Results Using Hierarchical RNN with Query-aware Attention

Songwei Ge, Zhicheng Dou, Zhengbao Jiang +2

Search results personalization has become an effective way to improve the quality of search engines. Previous studies extracted information such as past clicks, user topical intere…

cs.IR2019

From Text to Sound: A Preliminary Study on Retrieving Sound Effects to Radio Stories

Songwei Ge, Curtis Xuan, Ruihua Song +3

Sound effects play an essential role in producing high-quality radio stories but require enormous labor cost to add. In this paper, we address the problem of automatically adding s…

cs.LG2019★ 2 cited

Developing Creative AI to Generate Sculptural Objects

Songwei Ge, Austin Dill, Eunsu Kang +4

We explore the intersection of human and machine creativity by generating sculptural objects through machine learning. This research raises questions about both the technical detai…

cs.CV2019★ 271 cited

Learning Robust Global Representations by Penalizing Local Predictive Power

Haohan Wang, Songwei Ge, Eric P. Xing +1

Despite their renowned predictive power on i.i.d. data, convolutional neural networks are known to rely more on high-frequency patterns that humans deem superficial than on low-fre…