Sebastian Proksch
Information Systems · 2015–2021
A researcher in the Science corpus: 5 papers; trusts 37 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 57 citations into it; #2,760 of 8,771 by trust here, #4,012 by citations
- Artificial Intelligence — 41 citations into it
- Software — 30 citations into it
- Natural Language Processing — 22 citations into it; #4,122 of 5,688 by trust here, #4,983 by citations
- Code Generation & Program Synthesis — 17 citations into it
- Computer Networks and Communications — 16 citations into it; #4,222 of 9,886 by trust here, #4,594 by citations
- Program Analysis & Verification — 15 citations into it
- Signal Processing — 15 citations into it
Whom Sebastian Proksch trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Premkumar T. Devanbu
- Romain Robbes
- Marcel Bruch
- Veselin Raychev
- Thomas M. Cover
- Stanley F. Chen
- Olivier Chapelle
- Tung Thanh Nguyen
- Raymond P. L. Buse
- John Millar Carroll
Who trusts Sebastian Proksch overall
- Vincent J. Hellendoorn
- Sven Amann
- Miltiadis Allamanis
- Seohyun Kim
- Earl T. Barr
- Sarah Nadi
- Harald C. Gall
- Alexey Svyatkovskiy
- Jinman Zhao
- Frank F. Xu
Papers from Sebastian Proksch's perspective
Ordered by how strongly the researchers Sebastian Proksch trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
Their papers
- Intelligent Code Completion with Bayesian Networks (2015) — 92 citations
- Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python (2021) — 77 citations
- When Code Completion Fails: A Case Study on Real-World Completions (2019) — 86 citations
- A Study of Visual Studio Usage in Practice (2016) — 91 citations
- Evaluating the evaluations of code recommender systems: A reality check (2016) — 27 citations