activity
20082026
most citedHierarchical Amortized Training for Memory-efficient High Resolution 3D GAN

128 citations · 877 across the 52 of their papers we have counts for

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Showing 2022Show all

12 papers · 1 filter

cs.SD2022★ 1 cited

BER: Balanced Error Rate For Speaker Diarization

Tao Liu, Kai Yu

DER is the primary metric to evaluate diarization performance while facing a dilemma: the errors in short utterances or segments tend to be overwhelmed by longer ones. Short segmen…

eess.AS2022

EmoDiff: Intensity Controllable Emotional Text-to-Speech with Soft-Label Guidance

Yiwei Guo, Chenpeng Du, Xie Chen +1

Although current neural text-to-speech (TTS) models are able to generate high-quality speech, intensity controllable emotional TTS is still a challenging task. Most existing method…

cs.NI2022★ 3 cited

Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks

Liu Yang, Yun Li, Simon X. Yang +3

Emerging six generation (6G) is the integration of heterogeneous wireless networks, which can seamlessly support anywhere and anytime networking. But high Quality-of-Trust should b…

cs.NI2022★ 95 cited

An Intelligent Deterministic Scheduling Method for Ultra-Low Latency Communication in Edge Enabled Industrial Internet of Things

Yinzhi Lu, Liu Yang, Simon X. Yang +4

Edge enabled Industrial Internet of Things (IIoT) platform is of great significance to accelerate the development of smart industry. However, with the dramatic increase in real-tim…

q-bio.BM2022

Hyperbolic Molecular Representation Learning for Drug Repositioning

Ke Yu, Shyam Visweswaran, Kayhan Batmanghelich

Learning accurate drug representations is essential for task such as computational drug repositioning. A drug hierarchy is a valuable source that encodes knowledge of relations amo…

eess.IV2022

Context-aware Self-supervised Learning for Medical Images Using Graph Neural Network

Li Sun, Ke Yu, Kayhan Batmanghelich

Although self-supervised learning enables us to bootstrap the training by exploiting unlabeled data, the generic self-supervised methods for natural images do not sufficiently inco…