Ichigaku Takigawa

Computational Theory and Mathematics · 2009–2020

A researcher in the Science corpus: 6 papers; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 40 citations into it
• Molecular Biology — 39 citations into it
• Artificial Intelligence — 14 citations into it
• Statistical Learning Theory — 7 citations into it
• Evaluation & Benchmarks — 5 citations into it
• Genetics — 5 citations into it
• Statistics and Probability — 5 citations into it

Whom Ichigaku Takigawa trusts overall

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

1. Vladimir Naumovich Vapnik
2. Christopher K. I. Williams
3. Bernhard Schölkopf
4. Kristin P. Bennett
5. Geoffrey J. McLachlan
6. Eric R. Ziegel
7. Luc Devroye
8. Carey E. Priebe
9. Chih-Jen Lin
10. Alex Smola

Who trusts Ichigaku Takigawa overall

1. Masashi Tsubaki

Papers from Ichigaku Takigawa's perspective

Ordered by how strongly the researchers Ichigaku Takigawa trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
9. LIBSVM: A library for support vector machines
10. Statistical learning theory

Their papers

• Similarity-based machine learning methods for predicting drug-target interactions: a brief review (2014) — 384 citations
• Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data (2009) — 25 citations
• Machine Learning for Catalysis Informatics: Recent Applications and Prospects (2020) — 482 citations
• Density Functional Theory Calculations of Oxygen Vacancy Formation and Subsequent Molecular Adsorption on Oxide Surfaces (2018) — 170 citations
• Toward Effective Utilization of Methane: Machine Learning Prediction of Adsorption Energies on Metal Alloys (2018) — 152 citations
• Convex sets as prototypes for classifying patterns (2009) — 17 citations