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Symbolic Semantics for Probabilistic Programs
We present a new symbolic execution semantics of probabilistic programs that include observe statements and sampling from continuous distributions....
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An Interpretable Neuro-symbolic Model for Raven’s Progressive Matrices Reasoning
Raven’s Progressive Matrices (RPM) have been widely used as standard intelligence tests for human participants. Humans solve RPM problems in a...
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HESIP: A Hybrid System for Explaining Sub-symbolic Predictions
Machine learning models such as neural networks have been successfully used in many application domains such as mission critical systems, digital...
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Fast Symbolic Computation of Bottom SCCs
The computation of bottom strongly connected components (BSCCs) is a fundamental task in model checking, as well as in characterizing the attractors...
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Symbolic Methods for Studying the Equilibrium Orientations of a System of Two Connected Bodies in a Circular Orbit
AbstractThis paper investigates the dynamics of a system of two bodies connected by a spherical hinge that moves along a circular orbit under the...
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Symbolic Studies of Maxwell’s Equations in Space-Time Algebra Formalism
AbstractDifferent implementations of Clifford algebra: spinors, quaternions, and geometric algebra, are used to describe physical and technical...
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Symbolic Reasoning About Quantum Circuits in Coq
A quantum circuit is a computational unit that transforms an input quantum state to an output state. A natural way to reason about its behavior is to...
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Symbolic Quantum Simulation with Quasimodo
The simulation of quantum circuits on classical computers is an important problem in quantum computing. Such simulation requires representations of...
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Automated Search for Vulnerabilities in ARM Software Using Dynamic Symbolic Execution
Abstract—Automated search for vulnerabilities in ARM IoT devices is considered. The problems of using symbolic execution for vulnerability detection...
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Decomposition of a Finite Quantum System into Subsystems: Symbolic–Numerical Approach
AbstractAny Hilbert space with composite dimension can be represented as a tensor product of Hilbert spaces of lower dimensions. This factorization...
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Generating Explanations for Conceptual Validation of Graph Neural Networks: An Investigation of Symbolic Predicates Learned on Relevance-Ranked Sub-Graphs
Graph Neural Networks (GNN) show good performance in relational data classification. However, their contribution to concept learning and the...
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Symbolic Model Checking Using Intervals of Vectors
Model checking is a powerful technique for software verification. However, the approach notably suffers from the infamous state space explosion...
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Vector Symbolic Architectures for Context-Free Grammars
Vector symbolic architectures (VSA) are a viable approach for the hyperdimensional representation of symbolic data, such as documents, syntactic...
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KLEEF: Symbolic Execution Engine (Competition Contribution)
KLEEF is a complete overhaul of the KLEE symbolic execution engine for LLVM, fine-tuned for a robust analysis of industrial C/C++ code. KLEEF...
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An Experimental Overview of Neural-Symbolic Systems
Neural-symbolic AI is the field that seeks to integrate deep learning with symbolic, logic-based methods, as they have complementary strengths....
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Interpretability in symbolic regression: a benchmark of explanatory methods using the Feynman data set
In some situations, the interpretability of the machine learning models plays a role as important as the model accuracy. Interpretability comes from...
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Fog computing application of cyber-physical models of IoT devices with symbolic approximation algorithms
Smart manufacturing systems based on cloud computing deal with large amounts of data for various IoT devices, resulting in several challenges,...
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Combining static analysis and dynamic symbolic execution in a toolchain to detect fault injection vulnerabilities
Certification through auditing allows to ensure that critical embedded systems are secure. This entails reviewing their critical components and...
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Stability and Zero-Hopf Bifurcation Analysis of the Lorenz–Stenflo System Using Symbolic Methods
This paper deals with the stability and zero-Hopf bifurcation of the Lorenz–Stenflo system by using methods of symbolic computation. Stability...
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Neuro Symbolic AI for Sequential Decision Making
Deep learning based approaches have been used to address several problems of a sequential nature, whether using supervised learning to learn a model...