Martin Erwig

Artificial Intelligence · 2000–2019

A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it; #30,406 of 35,345 by trust here, #33,294 by citations
• Program Analysis & Verification — 12 citations into it; #235 of 301 by trust here, #274 by citations
• Information Systems — 8 citations into it; #7,243 of 8,771 by trust here, #6,195 by citations
• Software Engineering — 7 citations into it; #91 of 113 by trust here, #98 by citations
• Hardware and Architecture — 5 citations into it

Whom Martin Erwig trusts overall

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

1. Jeremy G. Siek
2. Ronald Garcia

Who trusts Martin Erwig overall

1. Ming-Ho Yee

Papers from Martin Erwig's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Gradual Typing for Functional Languages
3. Human-level control through deep reinforcement learning
4. Gradual Typing for Objects (European Conference on Object-Oriented Programming)
5. Gradual typing with unification-based inference
6. The ins and outs of gradual type inference
7. Principal Type Schemes for Gradual Programs
8. On-line Q-learning using connectionist systems
9. On the Convergence of Stochastic Iterative Dynamic Programming Algorithms
10. Sound, heuristic type annotation inference for Ruby

Their papers

• Explainable Reinforcement Learning via Reward Decomposition (2019)
• Migrating gradual types (2017) — 22 citations
• The state of the art in end-user software engineering (2011) — 809 citations
• A foundation for representing and querying moving objects (2000) — 859 citations