Tim Mueller

Materials Chemistry · 2010–2020

A researcher in the Science corpus: 8 papers; trusts 10 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 108 citations into it; #2,963 of 11,513 by trust here, #4,577 by citations
• Electrical and Electronic Engineering — 55 citations into it
• Atomic and Molecular Physics, and Optics — 41 citations into it
• Computational Theory and Mathematics — 28 citations into it
• Catalysis — 15 citations into it
• AI for Physical Sciences — 14 citations into it
• Automotive Engineering — 14 citations into it

Whom Tim Mueller trusts overall

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

1. J. Behler
2. Gerbrand Ceder
3. David D. Lewis
4. W. Setyawan
5. K. Momma
6. H. Sebastian Seung
7. Shyue Ping Ong
8. Isabelle M Guyon
9. A. P. Bart'ok
10. Leo Breiman

Who trusts Tim Mueller overall

1. Yuri Mishin
2. Rampi Ramprasad
3. D. Tourret
4. Rohit Batra
5. Ghanshyam Pilania
6. Hong Liu
7. Stefano Curtarolo
8. A. Mannodi‐Kanakkithodi
9. V. Botu

Papers from Tim Mueller's perspective

Ordered by how strongly the researchers Tim Mueller 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Query by committee
6. Regression Shrinkage and Selection via the Lasso
7. The Nature of Statistical Learning Theory
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet Large Scale Visual Recognition Challenge
10. ImageNet: A large-scale hierarchical image database

Their papers

• Finding Nature’s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory (2010) — 514 citations
• Machine Learning in Materials Science (2016) — 337 citations
• Machine learning for interatomic potential models. (2020) — 308 citations
• High-performance transition metal–doped Pt3Ni octahedra for oxygen reduction reaction (2015) — 1,672 citations
• Evaluation of Tavorite-Structured Cathode Materials for Lithium-Ion Batteries Using High-Throughput Computing (2011) — 265 citations
• Low-Overpotential Electroreduction of Carbon Monoxide Using Copper Nanowires (2017) — 146 citations
• A high-throughput infrastructure for density functional theory calculations (2011)
• Finding Nature′s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory. (2010) — 22 citations