53 citations · 145 across the 24 of their papers we have counts for
4 papers · 1 filter
Formalizing Statistical Causality via Modal Logic
Yusuke Kawamoto, Tetsuya Sato, Kohei Suenaga
We propose a formal language for describing and explaining statistical causality. Concretely, we define Statistical Causality Language (StaCL) for expressing causal effects and spe…
Sound and Relatively Complete Belief Hoare Logic for Statistical Hypothesis Testing Programs
Yusuke Kawamoto, Tetsuya Sato, Kohei Suenaga
We propose a new approach to formally describing the requirement for statistical inference and checking whether a program uses the statistical method appropriately. Specifically, w…
Learning Heuristics for Template-based CEGIS of Loop Invariants with Reinforcement Learning
Minchao Wu, Takeshi Tsukada, Hiroshi Unno +2
Loop-invariant synthesis is the basis of program verification. Due to the undecidability of the problem in general, a tool for invariant synthesis necessarily uses heuristics. Desp…
Automated proof synthesis for propositional logic with deep neural networks
Taro Sekiyama, Kohei Suenaga
This work explores the application of deep learning, a machine learning technique that uses deep neural networks (DNN) in its core, to an automated theorem proving (ATP) problem. T…