Sandip De
Computational Chemistry & Drug Discovery · 2015–2019
A researcher in the Science corpus: 3 papers; trusts 5 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computational Chemistry & Drug Discovery — 25 citations into it; #289 of 425 by trust here, #125 by citations
- Computational Theory and Mathematics — 23 citations into it; #9,561 of 12,182 by trust here, #898 by citations
- Physical and Theoretical Chemistry — 12 citations into it
- Computer Vision and Pattern Recognition — 8 citations into it
- Spectroscopy — 8 citations into it
- Artificial Intelligence — 7 citations into it
- Statistical Learning Theory — 5 citations into it
Whom Sandip De trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Eric R. Ziegel
- W. L. Jorgensen
- Christopher K. I. Williams
- Carl E. Rasmussen
- Marco Cuturi
- A. P. Bart'ok
- J. Behler
- Michele Ceriotti
- Matthias Rupp
Who trusts Sandip De overall
- Pascal Friederich
- Matthew J. Hirn
- Félix Musil
- Aldo Glielmo
- Rampi Ramprasad
- Kevin Ryczko
- A. P. Bart'ok
- M. J. Willatt
- Florian Hase
- Stefan Chmiela
Papers from Sandip De's perspective
Ordered by how strongly the researchers Sandip De trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- The Elements of Statistical Learning
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
- Harmonic Analysis on Semigroups
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Machine learning unifies the modeling of materials and molecules (2017) — 652 citations
- Comparing molecules and solids across structural and alchemical space. (2015) — 593 citations
- Promoting transparency and reproducibility in enhanced molecular simulations (2019) — 1,046 citations