research
∙
07/15/2023
Probabilistic Black-Box Checking via Active MDP Learning
We introduce a novel methodology for testing stochastic black-box system...
share
research
∙
01/10/2023
Learning nonlinear hybrid automata from input–output time-series data
Learning an automaton that approximates the behavior of a black-box syst...
research
∙
10/31/2022
BOREx: Bayesian-Optimization–Based Refinement of Saliency Map for Image- and Video-Classification Models
Explaining a classification result produced by an image- and video-class...
research
∙
10/30/2022
Formalizing Statistical Causality via Modal Logic
We propose a formal language for describing and explaining statistical c...
research
∙
08/15/2022
Sound and Relatively Complete Belief Hoare Logic for Statistical Hypothesis Testing Programs
We propose a new approach to formally describing the requirement for sta...
research
∙
07/06/2022
Goal-Aware RSS for Complex Scenarios via Program Logic
We introduce a goal-aware extension of responsibility-sensitive safety (...
research
∙
06/03/2022
Oblivious Online Monitoring for Safety LTL Specification via Fully Homomorphic Encryption
In many Internet of Things (IoT) applications, data sensed by an IoT dev...
research
∙
03/27/2022
The Lattice-Theoretic Essence of Property Directed Reachability Analysis
We present LT-PDR, a lattice-theoretic generalization of Bradley's prope...
research
∙
09/10/2021
Efficient Black-Box Checking via Model Checking with Strengthened Specifications
Black-box checking (BBC) is a testing method for cyber-physical systems ...
research
∙
08/30/2021
HELMHOLTZ: A Verifier for Tezos Smart Contracts Based on Refinement Types
A smart contract is a program executed on a blockchain, based on which m...
research
∙
07/16/2021
Enhancing Loop-Invariant Synthesis via Reinforcement Learning
Loop-invariant synthesis is the basis of every program verification proc...
research
∙
06/09/2021
Verification of a Merkle Patricia Tree Library Using F*
A Merkle tree is a data structure for representing a key-value store as ...
research
∙
01/05/2021
Control-Data Separation and Logical Condition Propagation for Efficient Inference on Probabilistic Programs
We introduce a novel sampling algorithm for Bayesian inference on impera...
research
∙
10/06/2020
Visualizing Color-wise Saliency of Black-Box Image Classification Models
Image classification based on machine learning is being commonly used. H...
research
∙
02/18/2020
ConSORT: Context- and Flow-Sensitive Ownership Refinement Types for Imperative Programs
We present ConSORT, a type system for safety verification in the presenc...
research
∙
10/09/2019
Generalized Property-Directed Reachability for Hybrid Systems
Generalized property-directed reachability (GPDR) belongs to the family ...
research
∙
05/30/2018
Automated proof synthesis for propositional logic with deep neural networks
This work explores the application of deep learning, a machine learning ...
research
∙
06/20/2017
Towards Proof Synthesis Guided by Neural Machine Translation for Intuitionistic Propositional Logic
Inspired by the recent evolution of deep neural networks (DNNs) in machi...
research
∙
04/25/2016
