D. Kov'acs

Materials Chemistry · 2022–2023

A researcher in the Science corpus: 3 papers; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 105 citations into it
• Atomic and Molecular Physics, and Optics — 39 citations into it
• Computational Theory and Mathematics — 35 citations into it
• Molecular Biology — 26 citations into it
• Computational Chemistry & Drug Discovery — 24 citations into it
• Physical and Theoretical Chemistry — 22 citations into it
• AI for Physical Sciences — 11 citations into it
• Spectroscopy — 8 citations into it

Whom D. Kov'acs trusts overall

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

1. Johannes Klicpera
2. Kristof T. Schütt
3. Alexander V. Shapeev
4. J. Behler
5. Ralf Drautz
6. Risi Kondor
7. A. P. Bart'ok
8. Stefan Chmiela
9. Aidan P. Thompson
10. Albert Musaelian

Papers from D. Kov'acs's perspective

Ordered by how strongly the researchers D. Kov'acs 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. Neural Message Passing for Quantum Chemistry (International Conference on Machine Learning)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields (2022) — 1,193 citations
• A foundation model for atomistic materials chemistry. (2023) — 653 citations
• The design space of E(3)-equivariant atom-centred interatomic potentials (2022) — 361 citations