Jian Cong

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 3 papers; trusts 30 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 72 citations into it
• Signal Processing — 52 citations into it
• Speech & Audio — 45 citations into it
• Generative Models — 38 citations into it
• Computer Vision and Pattern Recognition — 22 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it

Whom Jian Cong trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Ryuichi Yamamoto
5. Alex Krizhevsky
6. Alex Graves
7. Individualized Treat
8. Yann LeCun
9. Karen Simonyan
10. Ilya Sutskever

Who trusts Jian Cong overall

1. Xu Tan
2. Yanqing Liu
3. Tao Qin
4. Rui Xue

Papers from Jian Cong's perspective

Ordered by how strongly the researchers Jian Cong 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. GENERATIVE ADVERSARIAL NETS
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• NaturalSpeech: End-to-End Text-to-Speech Synthesis With Human-Level Quality (2022) — 351 citations
• Glow-WaveGAN: Learning Speech Representations from GAN-based Variational Auto-Encoder For High Fidelity Flow-based Speech Synthesis (2021) — 29 citations
• Data Efficient Voice Cloning from Noisy Samples with Domain Adversarial Training (2020) — 33 citations