Hanbin Bae

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it
• Signal Processing — 27 citations into it
• Speech & Audio — 23 citations into it
• Generative Models — 16 citations into it
• Model Architectures — 5 citations into it

Whom Hanbin Bae trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Truong Q. Nguyen
4. Naihan Li
5. Yoshua Bengio
6. Individualized Treat
7. Jimmy Ba
8. Aäron van den Oord
9. Alex Krizhevsky
10. Ilya Loshchilov

Who trusts Hanbin Bae overall

1. Yanli Li
2. Xu Tan

Papers from Hanbin Bae's perspective

Ordered by how strongly the researchers Hanbin Bae trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. GENERATIVE ADVERSARIAL NETS
7. Gradient-based learning applied to document recognition
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Avocodo: Generative Adversarial Network for Artifact-free Vocoder (2022) — 45 citations
• Speaking Speed Control of End-to-End Speech Synthesis using Sentence-Level Conditioning (2020) — 19 citations