Qiao Tian
Artificial Intelligence · 2018–2023
A researcher in the Science corpus: 7 papers; trusts 83 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 160 citations into it; #24,007 of 35,345 by trust here, #18,586 by citations
- Signal Processing — 100 citations into it; #4,977 of 7,572 by trust here, #4,201 by citations
- Speech & Audio — 86 citations into it
- Computer Vision and Pattern Recognition — 67 citations into it
- Generative Models — 41 citations into it
- Natural Language Processing — 36 citations into it
- Model Architectures — 25 citations into it
Whom Qiao Tian trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Alex Graves
- Yoshua Bengio
- Aäron van den Oord
- Alex Krizhevsky
- Jimmy Ba
- Ilya Sutskever
- Oriol Vinyals
- Individualized Treat
Who trusts Qiao Tian overall
- Ryuichi Yamamoto
- Xu Tan
- Eunwoo Song
- Yibin Zheng
- Cong Wang
- Jae-Min Kim
- Tao Qin
- Zewang Zhang
- Zhaoxi Mu
- Xinhui Li
Papers from Qiao Tian's perspective
Ordered by how strongly the researchers Qiao Tian trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- PolyVoice: Language Models for Speech to Speech Translation (2023) — 35 citations
- AudioLDM 2: Learning Holistic Audio Generation With Self-Supervised Pretraining (2023) — 512 citations
- LM-VC: Zero-Shot Voice Conversion via Speech Generation Based on Language Models (2023) — 47 citations
- FeatherTTS: Robust and Efficient attention based Neural TTS (2020) — 5 citations
- FeatherWave: An efficient high-fidelity neural vocoder with multi-band linear prediction (2020) — 22 citations
- AdaDurIAN: Few-shot Adaptation for Neural Text-to-Speech with DurIAN (2020) — 27 citations
- Generative Adversarial Network based Speaker Adaptation for High Fidelity WaveNet Vocoder (2018) — 9 citations