Simon Johansson

Computational Theory and Mathematics · 2019

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 42 citations into it
• Model Architectures — 8 citations into it

Whom Simon Johansson trusts overall

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

1. Diederik P. Kingma
2. Peter Ertl
3. Ronald J. Williams
4. Sepp Hochreiter
5. Geoffrey E. Hinton
6. Andrew L. Maas
7. David Weininger
8. Yoshua Bengio
9. J. Urgen Schmidhuber
10. Jimmy Ba

Papers from Simon Johansson's perspective

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

1. Long Short-Term Memory
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. GENERATIVE ADVERSARIAL NETS

Their papers

• A de novo molecular generation method using latent vector based generative adversarial network (2019) — 356 citations
• Randomized SMILES strings improve the quality of molecular generative models (2019) — 340 citations