Bogdan Vasilescu
Artificial Intelligence · 2015–2023
A researcher in the Science corpus: 7 papers; trusts 100 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 100 citations into it; #10,530 of 35,345 by trust here, #10,430 by citations
- Information Systems — 100 citations into it; #1,315 of 8,771 by trust here, #1,025 by citations
- Natural Language Processing — 85 citations into it; #2,615 of 5,688 by trust here, #2,364 by citations
- Code Generation & Program Synthesis — 42 citations into it; #190 of 220 by trust here, #190 by citations
- Computer Science Applications — 33 citations into it
- Software — 31 citations into it; #909 of 1,227 by trust here, #718 by citations
- Computer Vision and Pattern Recognition — 17 citations into it
- Signal Processing — 15 citations into it
Whom Bogdan Vasilescu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Georgios Gousios
- Premkumar T. Devanbu
- Miltiadis Allamanis
- Philipp Koehn
- Franz Joseph Och
- Veselin Raychev
- Daniel Marcu
- Christian Bird
- Diederik P. Kingma
- Yoshua Bengio
Who trusts Bogdan Vasilescu overall
- Michael Pradel
- Koushik Sen
- Miltiadis Allamanis
- Rohan Bavishi
- Georgios Gousios
- Baptiste Rozière
- Vincent J. Hellendoorn
- Rafael-Michael Karampatsis
- Earl T. Barr
- Hlib Babii
Papers from Bogdan Vasilescu's perspective
Ordered by how strongly the researchers Bogdan Vasilescu trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
Their papers
- Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow (2018) — 366 citations
- Incorporating External Knowledge through Pre-training for Natural Language to Code Generation (2020) — 88 citations
- Using an LLM to Help with Code Understanding (2023) — 626 citations
- In-IDE Code Generation from Natural Language: Promise and Challenges (2021) — 186 citations
- Recovering clear, natural identifiers from obfuscated JS names (2017) — 71 citations
- Quality and productivity outcomes relating to continuous integration in GitHub (2015) — 441 citations
- Gender and Tenure Diversity in GitHub Teams (2015) — 394 citations