Kevin Ryczko

Materials Chemistry · 2017

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 17 citations into it
• Computational Chemistry & Drug Discovery — 11 citations into it

Whom Kevin Ryczko trusts overall

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

1. A. P. Bart'ok
2. Matthias Rupp 
3. J. Perdew
4. Alexandre Tkatchenko
5. Sandip De
6. Stefan Chmiela
7. Rafael Gómez‐Bombarelli
8. Li Li
9. Gábor Csányi
10. Kieron Burke

Papers from Kevin Ryczko's perspective

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

1. Human-level control through deep reinforcement learning
2. Scikit-learn: Machine Learning in Python
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Mastering the game of Go with deep neural networks and tree search
5. Gradient-based learning applied to document recognition
6. Fast and accurate modeling of molecular atomization energies with machine learning.
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Machine learning of accurate energy-conserving molecular force fields
9. Attention is All you Need (Neural Information Processing Systems)
10. Generalized Gradient Approximation Made Simple.

Their papers

• Convolutional neural networks for atomistic systems (2017) — 44 citations