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Found 7 papers, 0 papers with code
Towards Global Neural Network Abstractions with Locally-Exact Reconstruction
Unfortunately, existing abstraction techniques are slack, which limits their applicability to small local regions of the input domain.
CEG4N: Counter-Example Guided Neural Network Quantization Refinement
Existing quantization techniques tend to degrade the network accuracy.
QNNVerifier: A Tool for Verifying Neural Networks using SMT-Based Model Checking
QNNVerifier is the first open-source tool for verifying implementations of neural networks that takes into account the finite word-length (i. e. quantization) of their operands.
Verifying Quantized Neural Networks using SMT-Based Model Checking
Furthermore, for small- to medium-sized ANN, our approach completes most of its verification runs in minutes.
Evolving Fuzzy System Applied to Battery Charge Capacity Prediction for Fault Prognostics
In such problems, accurate predictions of multiple steps ahead are essential for the Remaining Useful Life (RUL) estimation of a given asset.
Incremental Learning and State-Space Evolving Fuzzy Control of Nonlinear Time-Varying Systems with Unknown Model
We present a method for incremental modeling and time-varying control of unknown nonlinear systems.
Incremental Verification of Fixed-Point Implementations of Neural Networks
We have implemented the proposed approach on top of the efficient SMT-based bounded model checker (ESBMC), and its experimental results show that it can successfully verify safety properties, in actual implementations of ANNs, and generate real adversarial cases in MLPs.
