# Jun Wang

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/jun-wang-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 4,030 |
| Field | Topic Modeling |
| h-index | 31 |
| i10-index | 83 |
| Last Known Institution | Ludong University |
| OpenAlex ID | https://openalex.org/A5110195480 |
| ORCID iD | 0000-0001-8932-6661 |
| Works | 296 |

## Researcher papers

- [Long Text Generation via Adversarial Training with Leaked Information](https://scholariq.org/papers/long-text-generation-via-adversarial-training-with-leaked-information/)
- [Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition](https://scholariq.org/papers/dive-into-ambiguity-latent-distribution-mining-and-pairwise-uncertainty/)
- [ViTAA: Visual-Textual Attributes Alignment in Person Search by Natural Language](https://scholariq.org/papers/vitaa-visual-textual-attributes-alignment-in-person-search-by-natural-language/)
- [Multi-attribute fuzzy time series method based on fuzzy clustering](https://scholariq.org/papers/multi-attribute-fuzzy-time-series-method-based-on-fuzzy-clustering/)
- [Feature Selection by Maximizing Independent Classification Information](https://scholariq.org/papers/feature-selection-by-maximizing-independent-classification-information/)
- [Feature-Induced Partial Multi-label Learning](https://scholariq.org/papers/feature-induced-partial-multi-label-learning/)
- [PanGu-$α$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation](https://scholariq.org/papers/pangu-large-scale-autoregressive-pretrained-chinese-language-models-with-auto/)
- [Cross-Modal Prototype Driven Network for Radiology Report Generation](https://scholariq.org/papers/cross-modal-prototype-driven-network-for-radiology-report-generation/)
- [T-CNN: Trilinear convolutional neural networks model for visual detection of plant diseases](https://scholariq.org/papers/t-cnn-trilinear-convolutional-neural-networks-model-for-visual-detection-of/)
- [Deep Extractor Network for Target Speaker Recovery from Single Channel Speech Mixtures](https://scholariq.org/papers/deep-extractor-network-for-target-speaker-recovery-from-single-channel-speech/)

## Researcher topics

- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)
- [Natural Language Processing Techniques](https://scholariq.org/topics/natural-language-processing-techniques/)
- [Music and Audio Processing](https://scholariq.org/topics/music-and-audio-processing/)
- [Speech and Audio Processing](https://scholariq.org/topics/speech-and-audio-processing/)
- [Speech Recognition and Synthesis](https://scholariq.org/topics/speech-recognition-and-synthesis/)

## Researcher university

- [Ludong University](https://scholariq.org/institutions/ludong-university/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.