Igor I. Baskin
Computational Theory and Mathematics · 1997–2020
A researcher in the Science corpus: 7 papers; trusts 30 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Computational Theory and Mathematics — 145 citations into it; #7,634 of 12,182 by trust here, #1,379 by citations
- Materials Chemistry — 87 citations into it
- Artificial Intelligence — 66 citations into it
- Spectroscopy — 36 citations into it; #857 of 1,674 by trust here, #1,218 by citations
- Representation & Self-Supervised Learning — 24 citations into it
- Computer Vision and Pattern Recognition — 22 citations into it
- Model Architectures — 19 citations into it
- Optimization & Training — 16 citations into it
Whom Igor I. Baskin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Igor V. Tetko
- Geoffrey E. Hinton
- David John Cameron MacKay
- Kunihiko Fukushima
- Yann LeCun
- Mário A. T. Figueiredo
- Gary G. Yen
- Alex Krizhevsky
- Xavier Glorot
Who trusts Igor I. Baskin overall
- Gisbert Schneider
- Alexandru Korotcov
- Johannes Klicpera
- Marwin H. S. Segler
- David A. Winkler
- Paul Wrede
- Igor V. Tetko
- Valery Tkachenko
- Raquel Rodríguez-Pérez
Papers from Igor I. Baskin's perspective
Ordered by how strongly the researchers Igor I. Baskin 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)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Machine Learning Methods for Property Prediction in Chemoinformatics: Quo Vadis? (2012) — 220 citations
- QSAR Modeling: Where have you been? Where are you going to? (2014) — 1,811 citations
- A renaissance of neural networks in drug discovery (2016) — 213 citations
- QSAR without borders (2020) — 546 citations
- Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information (2011) — 610 citations
- A Neural Device for Searching Direct Correlations Between Structures and Properties of Chemical Compounds. (2010) — 7 citations
- A Neural Device for Searching Direct Correlations between Structures and Properties of Chemical Compounds (1997)