Jianzong Wang

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 7 papers; trusts 64 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 111 citations into it; #15,040 of 35,345 by trust here, #14,718 by citations
• Computer Vision and Pattern Recognition — 51 citations into it
• Signal Processing — 43 citations into it; #6,575 of 7,572 by trust here, #5,829 by citations
• Speech & Audio — 37 citations into it
• Natural Language Processing — 29 citations into it
• Generative Models — 25 citations into it
• Model Architectures — 18 citations into it
• Optimization & Training — 10 citations into it

Whom Jianzong Wang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Ilya Sutskever
5. Kaiming He
6. Aäron van den Oord
7. Alex Krizhevsky
8. Jimmy Ba
9. Alex Graves
10. Karen Simonyan

Who trusts Jianzong Wang overall

1. Xu Tan
2. Tao Qin
3. Yanli Li
4. Ulme Wennberg
5. Jaehyeon Kim
6. Isaac Elias
7. Zhaoxi Mu
8. Jonathan Shen
9. Won Jang
10. Frank K. Soong

Papers from Jianzong Wang's perspective

Ordered by how strongly the researchers Jianzong Wang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Going deeper with convolutions
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Aligntts: Efficient Feed-Forward Text-to-Speech System Without Explicit Alignment (2020) — 63 citations
• From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning (2023) — 373 citations
• Speech Representation Disentanglement with Adversarial Mutual Information Learning for One-shot Voice Conversion (2022) — 45 citations
• LVCNet: Efficient Condition-Dependent Modeling Network for Waveform Generation (2021) — 18 citations
• Prosody Learning Mechanism for Speech Synthesis System Without Text Length Limit (2020) — 9 citations
• IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge. (2020) — 366 citations
• GraphTTS: Graph-to-Sequence Modelling in Neural Text-to-Speech (2020) — 22 citations