Murray Shanahan

Artificial Intelligence · 1995–2023

A researcher in the Science corpus: 22 papers; trusts 813 researchers and is trusted by 56 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 376 citations into it; #4,646 of 35,345 by trust here, #2,747 by citations
• Computer Vision and Pattern Recognition — 198 citations into it; #7,027 of 21,575 by trust here, #3,929 by citations
• Reinforcement Learning — 162 citations into it; #864 of 2,242 by trust here, #535 by citations
• Cognitive Neuroscience — 67 citations into it
• Generative Models — 66 citations into it
• Representation & Self-Supervised Learning — 64 citations into it; #2,178 of 3,145 by trust here, #2,587 by citations
• Natural Language Processing — 62 citations into it; #2,502 of 5,688 by trust here, #2,307 by citations
• Large Language Models — 57 citations into it

Whom Murray Shanahan trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Alex Krizhevsky
5. Kaiming He
6. Yann LeCun
7. Ilya Sutskever
8. Alex Graves
9. Ruslan Salakhutdinov
10. Richard S. Sutton

Who trusts Murray Shanahan overall

1. Marta Garnelo
2. Anirudh Goyal
3. Jie Huang
4. Alessandro Lenci
5. Julien Pourcel
6. Mehrdad Farajtabar
7. Sjoerd van Steenkiste
8. Kai Arulkumaran
9. Kevin Chen-Chuan Chang
10. Zifeng Wang

Papers from Murray Shanahan's perspective

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

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

Their papers

• Towards Deep Symbolic Reinforcement Learning (2016) — 236 citations
• Conditional Neural Processes (2018) — 864 citations
• Relational Deep Reinforcement Learning (2018) — 245 citations
• Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning (2022) — 482 citations
• Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders (2016) — 734 citations
• Continual Reinforcement Learning with Complex Synapses (2018) — 102 citations
• SCAN: Learning Hierarchical Compositional Visual Concepts (2017) — 134 citations
• Faithful Reasoning Using Large Language Models (2022) — 163 citations
• Reconciling deep learning with symbolic artificial intelligence: representing objects and relations (2019) — 237 citations
• Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning (2017) — 103 citations
• Policy Consolidation for Continual Reinforcement Learning (2019) — 61 citations
• Encoders and Ensembles for Task-Free Continual Learning (2021) — 26 citations
• Role play with large language models (2023) — 609 citations
• Embodiment and the inner lifeCognition and Consciousness in the Space of Possible Minds (2010) — 113 citations
• Perception as Abduction: Turning Sensor Data Into Meaningful Representation (2005) — 157 citations
• Continual Reinforcement Learning with Multi-Timescale Replay (2020) — 18 citations
• Talking about Large Language Models (2022) — 479 citations
• Consistent Generative Query Networks (2018) — 42 citations
• Deep reinforcement learning with relational inductive biases (2018) — 231 citations
• Classifying Options for Deep Reinforcement Learning (2016) — 22 citations