Michael Heck

Artificial Intelligence · 2016–2022

A researcher in the Science corpus: 7 papers; trusts 50 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 141 citations into it; #15,631 of 35,345 by trust here, #14,718 by citations
• Natural Language Processing — 50 citations into it
• Meta & Continual Learning — 18 citations into it
• Reinforcement Learning — 17 citations into it
• Speech & Audio — 14 citations into it; #808 of 1,076 by trust here, #821 by citations
• Representation & Self-Supervised Learning — 13 citations into it; #2,264 of 3,145 by trust here, #2,805 by citations
• Management Science and Operations Research — 12 citations into it
• Signal Processing — 12 citations into it; #3,104 of 7,572 by trust here, #3,099 by citations

Whom Michael Heck trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Andreas Stolcke
4. Jimmy Ba
5. Yoshua Bengio
6. Alex Krizhevsky
7. Ilya Sutskever
8. Ashish Vaswani
9. Jacob Devlin
10. Ian H. Witten

Who trusts Michael Heck overall

1. Thomas Schatz
2. Morgane Rivière
3. Sakriani Watiasri Sakti
4. Emmanuel Dupoux
5. Jan Chorowski
6. Bin Wu
7. Shekhar Nayak
8. Andros Tjandra
9. Cory Shain
10. Shikib Mehri

Papers from Michael Heck's perspective

Ordered by how strongly the researchers Michael Heck 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. Attention is All you Need (Neural Information Processing Systems)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. ImageNet classification with deep convolutional neural networks
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. Gradient-based learning applied to document recognition
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Unsupervised Linear Discriminant Analysis for Supporting DPGMM Clustering in the Zero Resource Scenario (2016) — 36 citations
• TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking (2020) — 240 citations
• Feature optimized DPGMM clustering for unsupervised subword modeling: A contribution to zerospeech 2017 (2017) — 54 citations
• Dynamic Dialogue Policy for Continual Reinforcement Learning (2022) — 19 citations
• Dynamic Dialogue Policy Transformer for Continual Reinforcement Learning (2022)
• Domain-independent User Simulation with Transformers for Task-oriented Dialogue Systems (2021) — 37 citations
• Uncertainty Measures in Neural Belief Tracking and the Effects on Dialogue Policy Performance (2021) — 11 citations