Chiori Hori

Artificial Intelligence · 2012–2019

A researcher in the Science corpus: 6 papers; trusts 163 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 92 citations into it; #14,456 of 35,345 by trust here, #11,921 by citations
• Computer Vision and Pattern Recognition — 75 citations into it
• Natural Language Processing — 55 citations into it
• Evaluation & Benchmarks — 31 citations into it
• Model Architectures — 10 citations into it
• Representation & Self-Supervised Learning — 9 citations into it
• Large Language Models — 7 citations into it
• Signal Processing — 7 citations into it; #2,761 of 7,572 by trust here, #1,857 by citations

Whom Chiori Hori trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Karen Simonyan
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Oriol Vinyals
7. Ilya Sutskever
8. Dzmitry Bahdanau
9. Andrew Zisserman
10. Yann LeCun

Who trusts Chiori Hori overall

1. Aditya Mogadala
2. Chenyou Fan
3. Hung Le
4. Alex Falcon
5. X. Wang
6. Vivek Sharma
7. Wenzhong Guo
8. Zehua Sun
9. Haoxuan You
10. Khaled Bayoudh

Papers from Chiori Hori's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Attention-Based Multimodal Fusion for Video Description (2017) — 397 citations
• Audio Visual Scene-Aware Dialog (2019) — 230 citations
• End-to-end Audio Visual Scene-aware Dialog Using Multimodal Attention-based Video Features (2018) — 132 citations
• Dialog System Technology Challenge 7 (2019) — 38 citations
• Speech enhancement based on deep denoising autoencoder (2013) — 851 citations
• Factored recurrent neural network language model in TED lecture transcription (2012) — 12 citations