Erik T. Mueller

Artificial Intelligence · with Olabiyi · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 80 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 35 citations into it
• Natural Language Processing — 33 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Large Language Models — 8 citations into it
• Model Architectures — 7 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Erik T. Mueller trusts overall

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

1. Yoshua Bengio
2. Oriol Vinyals
3. Ilya Sutskever
4. Iulian Serban
5. Geoffrey E. Hinton
6. Quoc V. Le
7. Jiwei Li
8. Diederik P. Kingma
9. Alex Krizhevsky
10. Alex Graves

Papers from Erik T. Mueller's perspective

Ordered by how strongly the researchers Erik T. Mueller 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Multi-turn Dialogue Response Generation with Autoregressive Transformer Models (2019) — 13 citations
• A Persona-Based Multi-turn Conversation Model in an Adversarial Learning Framework (2018) — 10 citations