activity
20172021
most citedDeepTriage: Exploring the Effectiveness of Deep Learning for Bug Triaging

25 citations · 67 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.LG20212 cited

Deeplite Neutrino: An End-to-End Framework for Constrained Deep Learning Model Optimization

Anush Sankaran, Olivier Mastropietro, Ehsan Saboori +4

Designing deep learning-based solutions is becoming a race for training deeper models with a greater number of layers. While a large-size deeper model could provide competitive acc…

cs.LG2019

AuthorGAN: Improving GAN Reproducibility using a Modular GAN Framework

Raunak Sinha, Anush Sankaran, Mayank Vatsa +1

Generative models are becoming increasingly popular in the literature, with Generative Adversarial Networks (GAN) being the most successful variant, yet. With this increasing deman…

cs.LG201915 cited

Coverage Testing of Deep Learning Models using Dataset Characterization

Senthil Mani, Anush Sankaran, Srikanth Tamilselvam +1

Deep Neural Networks (DNNs), with its promising performance, are being increasingly used in safety critical applications such as autonomous driving, cancer detection, and secure au…

cs.LG2019

"You might also like this model": Data Driven Approach for Recommending Deep Learning Models for Unknown Image Datasets

Ameya Prabhu, Riddhiman Dasgupta, Anush Sankaran +2

For an unknown (new) classification dataset, choosing an appropriate deep learning architecture is often a recursive, time-taking, and laborious process. In this research, we propo…

cs.LG2018

Explaining Deep Learning Models using Causal Inference

Tanmayee Narendra, Anush Sankaran, Deepak Vijaykeerthy +1

Although deep learning models have been successfully applied to a variety of tasks, due to the millions of parameters, they are becoming increasingly opaque and complex. In order t…

cs.LG20177 cited

DLPaper2Code: Auto-generation of Code from Deep Learning Research Papers

Akshay Sethi, Anush Sankaran, Naveen Panwar +2

With an abundance of research papers in deep learning, reproducibility or adoption of the existing works becomes a challenge. This is due to the lack of open source implementations…