1 code implementation • 7 Apr 2023 • Zhe Tao, Stephanie Nawas, Jacqueline Mitchell, Aditya V. Thakur
The repair has the flexibility to modify multiple layers of the DNN, and runs in polynomial time.
2 code implementations • 9 Apr 2021 • Matthew Sotoudeh, Aditya V. Thakur
This has motivated a large number of techniques for finding unsafe behavior in DNNs.
1 code implementation • 9 Jan 2021 • Matthew Sotoudeh, Aditya V. Thakur
Formally, DNNs are complicated vector-valued functions which come in a variety of sizes and applications.
1 code implementation • 14 Sep 2020 • Matthew Sotoudeh, Aditya V. Thakur
In this paper, we argue that analogy making should be seen as a core primitive in software engineering.
1 code implementation • 12 Sep 2020 • Sung Kook Kim, Arnaud J. Venet, Aditya V. Thakur
We prove that our technique is optimal (i. e., it results in minimum memory footprint) for Bourdoncle's iteration strategy while computing the same result.
Programming Languages
1 code implementation • 11 Sep 2020 • Matthew Sotoudeh, Aditya V. Thakur
We present a framework parameterized by the abstract domain and activation functions used in the DNN that can be used to construct a corresponding ANN.
2 code implementations • 12 Sep 2019 • Sung Kook Kim, Arnaud J. Venet, Aditya V. Thakur
The de facto approach for computing the approximation of this fixpoint uses a sequential algorithm based on weak topological order (WTO).
Programming Languages
1 code implementation • 17 Aug 2019 • Matthew Sotoudeh, Aditya V. Thakur
Analysis and manipulation of trained neural networks is a challenging and important problem.
2 code implementations • NeurIPS 2019 • Matthew Sotoudeh, Aditya V. Thakur
A linear restriction of a function is the same function with its domain restricted to points on a given line.