Zobrazeno 1 - 10
of 134
pro vyhledávání: '"Thakur, Aditya"'
Density Functional Theory (DFT) is used extensively in the computation of electronic properties of matter, with various applications. Approximating the exchange-correlation (XC) functional is the key to the Kohn-Sham DFT approach, the basis of most D
Externí odkaz:
http://arxiv.org/abs/2408.05316
ResNets (or Residual Networks) are one of the most commonly used models for image classification tasks. In this project, we design and train a modified ResNet model for CIFAR-10 image classification. In particular, we aimed at maximizing the test acc
Externí odkaz:
http://arxiv.org/abs/2306.12100
Deep neural networks (DNNs) are becoming increasingly important components of software, and are considered the state-of-the-art solution for a number of problems, such as image recognition. However, DNNs are far from infallible, and incorrect behavio
Externí odkaz:
http://arxiv.org/abs/2304.03496
Autor:
AlOmar, Eman Abdullah, Ivanov, Anton, Kurbatova, Zarina, Golubev, Yaroslav, Mkaouer, Mohamed Wiem, Ouni, Ali, Bryksin, Timofey, Nguyen, Le, Kini, Amit, Thakur, Aditya
Refactoring is a critical task in software maintenance, and is usually performed to enforce better design and coding practices, while coping with design defects. The Extract Method refactoring is widely used for merging duplicate code fragments into
Externí odkaz:
http://arxiv.org/abs/2302.03416
Autor:
AlOmar, Eman Abdullah, Ivanov, Anton, Kurbatova, Zarina, Golubev, Yaroslav, Mkaouer, Mohamed Wiem, Ouni, Ali, Bryksin, Timofey, Nguyen, Le, Kini, Amit, Thakur, Aditya
We developed a plugin for IntelliJ IDEA called AntiCopyPaster, which tracks the pasting of code fragments inside the IDE and suggests the appropriate Extract Method refactoring to combat the propagation of duplicates. Unlike the existing approaches,
Externí odkaz:
http://arxiv.org/abs/2112.15230
Autor:
Sotoudeh, Matthew, Thakur, Aditya V.
Deep Neural Networks (DNNs) have grown in popularity over the past decade and are now being used in safety-critical domains such as aircraft collision avoidance. This has motivated a large number of techniques for finding unsafe behavior in DNNs. In
Externí odkaz:
http://arxiv.org/abs/2104.04413
Autor:
Sotoudeh, Matthew, Thakur, Aditya V.
Deep Neural Networks (DNNs) are rapidly gaining popularity in a variety of important domains. Formally, DNNs are complicated vector-valued functions which come in a variety of sizes and applications. Unfortunately, modern DNNs have been shown to be v
Externí odkaz:
http://arxiv.org/abs/2101.03263
Publikováno v:
International Journal of Medicine & Public Health. Apr-Jun2024, Vol. 14 Issue 2, p174-179. 6p.
Autor:
Sotoudeh, Matthew, Thakur, Aditya V.
An analogy is an identification of structural similarities and correspondences between two objects. Computational models of analogy making have been studied extensively in the field of cognitive science to better understand high-level human cognition
Externí odkaz:
http://arxiv.org/abs/2009.06592
Practical adoption of static analysis often requires trading precision for performance. This paper focuses on improving the memory efficiency of abstract interpretation without sacrificing precision or time efficiency. Computationally, abstract inter
Externí odkaz:
http://arxiv.org/abs/2009.05865