Thomas Joyce

Computer Vision and Pattern Recognition · 2015–2019

A researcher in the Science corpus: 4 papers; trusts 116 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 64 citations into it; #13,019 of 21,575 by trust here, #10,334 by citations
• Artificial Intelligence — 36 citations into it; #31,464 of 35,345 by trust here, #27,551 by citations
• Representation & Self-Supervised Learning — 21 citations into it
• Generative Models — 20 citations into it
• Model Architectures — 10 citations into it
• Media Technology — 5 citations into it

Whom Thomas Joyce trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Yann LeCun
6. Ilya Sutskever
7. Pascal Vincent
8. Jimmy Ba
9. Kaiming He
10. Ruslan Salakhutdinov

Who trusts Thomas Joyce overall

1. Onat Dalmaz
2. Maciej A. Mazurowski
3. Mahmut Yurt
4. Tao Zhou

Papers from Thomas Joyce's perspective

Ordered by how strongly the researchers Thomas Joyce 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Learning motion manifolds with convolutional autoencoders (2015) — 311 citations
• Disentangled representation learning in cardiac image analysis (2019) — 168 citations
• Factorised spatial representation learning: application in semi-supervised myocardial segmentation (2018) — 77 citations
• Multimodal MR Synthesis via Modality-Invariant Latent Representation (2017) — 347 citations