Chakkrit Kla Tantithamthavorn

Information Systems · 2016–2022

A researcher in the Science corpus: 5 papers; trusts 110 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 112 citations into it; #4,144 of 8,771 by trust here, #4,188 by citations
• Software — 96 citations into it; #568 of 1,227 by trust here, #512 by citations
• Artificial Intelligence — 62 citations into it
• Computer Networks and Communications — 35 citations into it; #8,003 of 9,886 by trust here, #7,492 by citations
• Statistics and Probability — 25 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Natural Language Processing — 10 citations into it

Whom Chakkrit Kla Tantithamthavorn trusts overall

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

1. Max Kuhn
2. Ewout W. Steyerberg
3. Martin J. Shepperd
4. Kaspar Rufibach
5. Marco D'Ambros
6. Shane McIntosh
7. Frauke Günther
8. Ahmed E. Hassan
9. Baljinder Ghotra
10. Stefan Lessmann

Who trusts Chakkrit Kla Tantithamthavorn overall

1. Ahmed E. Hassan
2. Ken-ichi Matsumoto
3. Shane McIntosh
4. Jaechang Nam
5. Wei Fu
6. Jian Zhang
7. Michael Fu
8. Tim Menzies

Papers from Chakkrit Kla Tantithamthavorn's perspective

Ordered by how strongly the researchers Chakkrit Kla Tantithamthavorn 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• LineVul: A Transformer-based Line-Level Vulnerability Prediction (2022) — 536 citations
• The Impact of Automated Parameter Optimization on Defect Prediction Models (2018) — 386 citations
• The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models (2018) — 295 citations
• An Empirical Comparison of Model Validation Techniques for Defect Prediction Models (2017) — 512 citations
• Automated Parameter Optimization of Classification Techniques for Defect Prediction Models (2016) — 353 citations