Hsin-Min Wang
Artificial Intelligence · 2015–2021
A researcher in the Science corpus: 8 papers; trusts 49 researchers and is trusted by 22 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 92 citations into it; #7,551 of 35,345 by trust here, #7,346 by citations
- Signal Processing — 88 citations into it; #2,606 of 7,572 by trust here, #981 by citations
- Speech & Audio — 52 citations into it; #652 of 1,076 by trust here, #590 by citations
- Computer Vision and Pattern Recognition — 25 citations into it; #12,916 of 21,575 by trust here, #10,334 by citations
- Natural Language Processing — 17 citations into it
- Generative Models — 14 citations into it; #1,174 of 1,956 by trust here, #1,163 by citations
- Representation & Self-Supervised Learning — 11 citations into it
- Model Architectures — 8 citations into it
Whom Hsin-Min Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Tomoki Toda
- Heiga Zen
- Keiichi Tokuda
- Hideki Kawahara
- Linghui Chen
- Max Welling
- Sam T. Roweis
Who trusts Hsin-Min Wang overall
- Junichi Yamagishi
- Berrak Sisman
- Hirokazu Kameoka
- Takuhiro Kaneko
- Chin-Cheng Hsu
- Xin Eric Wang
- Yi-Chiao Wu
- Hieu-Thi Luong
- Wei-Ning Hsu
- Hsin-Te Hwang
Papers from Hsin-Min Wang's perspective
Ordered by how strongly the researchers Hsin-Min Wang 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Auto-Encoding Variational Bayes (International Conference on Learning Representations)
- A Fast Learning Algorithm for Deep Belief Nets
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Voice Conversion from Unaligned Corpora Using Variational Autoencoding Wasserstein Generative Adversarial Networks (2017) — 326 citations
- Voice conversion from non-parallel corpora using variational auto-encoder (2016) — 319 citations
- Locally Linear Embedding for Exemplar-Based Spectral Conversion (2016) — 37 citations
- The AS-NU System for the M2VoC Challenge (2021)
- ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech (2019) — 651 citations
- MOSNet: Deep Learning based Objective Assessment for Voice Conversion (2019) — 373 citations
- Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks (2017) — 225 citations
- A probabilistic interpretation for artificial neural network-based voice conversion (2015) — 13 citations