Marvin Thielk

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 39 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 31 citations into it
• Generative Models — 28 citations into it
• Artificial Intelligence — 18 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Signal Processing — 10 citations into it

Whom Marvin Thielk trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yann LeCun
4. Yoshua Bengio
5. Alex Krizhevsky
6. Alec Radford
7. Radford M. Neal
8. Alex Graves
9. Kaiming He
10. L. V. D. van der Maaten

Papers from Marvin Thielk's perspective

Ordered by how strongly the researchers Marvin Thielk 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. GENERATIVE ADVERSARIAL NETS
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

• Generative adversarial interpolative autoencoding: adversarial training on latent space interpolations encourage convex latent distributions (2018) — 56 citations
• Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires (2020) — 304 citations