Rongjie Huang
Artificial Intelligence · 2021–2024
A researcher in the Science corpus: 16 papers; trusts 392 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 438 citations into it; #18,746 of 35,345 by trust here, #6,330 by citations
- Signal Processing — 340 citations into it; #3,105 of 7,572 by trust here, #538 by citations
- Speech & Audio — 281 citations into it; #862 of 1,076 by trust here, #325 by citations
- Generative Models — 183 citations into it; #1,400 of 1,956 by trust here, #696 by citations
- Computer Vision and Pattern Recognition — 180 citations into it; #21,531 of 21,575 by trust here, #11,083 by citations
- Natural Language Processing — 65 citations into it
- Model Architectures — 47 citations into it
- Representation & Self-Supervised Learning — 43 citations into it
Whom Rongjie Huang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Kaiming He
- Ilya Sutskever
- Aäron van den Oord
- Alex Graves
- Yann LeCun
- Oriol Vinyals
Who trusts Rongjie Huang overall
- Dongchao Yang
- Yi Ren
- Zhou Zhao
- Jinglin Liu
- Cong Han
- Ziyue Jiang
- Shengqiong Wu
- Zeqian Ju
- Sanyuan Chen
- Ya-Zhen Song
Papers from Rongjie Huang's perspective
Ordered by how strongly the researchers Rongjie Huang 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
- 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
- Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models (2023) — 505 citations
- Bilateral Denoising Diffusion Models (2021) — 47 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
- Mega-TTS: Zero-Shot Text-to-Speech at Scale with Intrinsic Inductive Bias (2023) — 101 citations
- Make-A-Voice: Unified Voice Synthesis With Discrete Representation (2023) — 38 citations
- InstructTTS: Modelling Expressive TTS in Discrete Latent Space With Natural Language Style Prompt (2023) — 174 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
- FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesis (2022) — 237 citations
- TranSpeech: Speech-to-Speech Translation With Bilateral Perturbation (2022) — 56 citations
- ProDiff: Progressive Fast Diffusion Model for High-Quality Text-to-Speech (2022) — 259 citations
- GenerSpeech: Towards Style Transfer for Generalizable Out-Of-Domain Text-to-Speech Synthesis (2022) — 36 citations
- M4Singer: A Multi-Style, Multi-Singer and Musical Score Provided Mandarin Singing Corpus (2022) — 123 citations
- SingGAN: Generative Adversarial Network For High-Fidelity Singing Voice Generation (2021) — 74 citations
- Multi-Singer: Fast Multi-Singer Singing Voice Vocoder With A Large-Scale Corpus (2021) — 135 citations