Nicola Molinari
Materials Chemistry · 2018–2021
A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Materials Chemistry — 28 citations into it
- Physical and Theoretical Chemistry — 6 citations into it
Whom Nicola Molinari trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Ralf Drautz (in Materials Chemistry)
Papers from Nicola Molinari's perspective
Ordered by how strongly the researchers Nicola Molinari trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gaussian Error Linear Units (GELUs)
- Neural Message Passing for Quantum Chemistry (International Conference on Machine Learning)
- Cormorant: Covariant Molecular Neural Networks
- SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
- PyTorch: An Imperative Style, High-Performance Deep Learning Library
- Gaussian approximation potentials: the accuracy of quantum mechanics, without the electrons.
- Directional Message Passing for Molecular Graphs (International Conference on Learning Representations)
- Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics
- Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network