Dongchao Yang
Artificial Intelligence · 2022–2024
A researcher in the Science corpus: 12 papers; trusts 248 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 382 citations into it
- Signal Processing — 279 citations into it; #7,258 of 7,572 by trust here, #805 by citations
- Speech & Audio — 226 citations into it; #921 of 1,076 by trust here, #322 by citations
- Computer Vision and Pattern Recognition — 145 citations into it
- Generative Models — 135 citations into it
- Large Language Models — 51 citations into it
- Representation & Self-Supervised Learning — 38 citations into it
- Statistical and Nonlinear Physics — 25 citations into it
Whom Dongchao Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Aäron van den Oord
- Alex Krizhevsky
- Jimmy Ba
- Oriol Vinyals
- Ilya Sutskever
- Jonathan Ho
- Kaiming He
Who trusts Dongchao Yang overall
- Rongjie Huang
- Zeqian Ju
- Xu Tan
- Sanyuan Chen
- Songxiang Liu
- Yuancheng Wang
- Detai Xin
- Cong Han
- Xin Zhang
- Deepanway Ghosal
Papers from Dongchao Yang's perspective
Ordered by how strongly the researchers Dongchao Yang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Diffsound: Discrete Diffusion Model for Text-to-Sound Generation (2022) — 434 citations
- Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models (2023) — 505 citations
- AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head (2023) — 405 citations
- HiFi-Codec: Group-residual Vector quantization for High Fidelity Audio Codec (2023) — 231 citations
- Make-A-Voice: Unified Voice Synthesis With Discrete Representation (2023) — 38 citations
- NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models (2024) — 403 citations
- InstructTTS: Modelling Expressive TTS in Discrete Latent Space With Natural Language Style Prompt (2023) — 174 citations
- RALL-E: Robust Codec Language Modeling with Chain-of-Thought Prompting for Text-to-Speech Synthesis (2024) — 44 citations
- Make-A-Voice: Revisiting Voice Large Language Models as Scalable Multilingual and Multitask Learners (2024) — 13 citations
- UniAudio: An Audio Foundation Model Toward Universal Audio Generation (2023) — 215 citations
- PromptTTS 2: Describing and Generating Voices with Text Prompt (2023) — 87 citations
- NADiffuSE: Noise-aware Diffusion-based Model for Speech Enhancement (2023) — 6 citations