5 citations · 12 across the 7 of their papers we have counts for
5 papers · 1 filter
Modeling Functional Similarity in Source Code with Graph-Based Siamese Networks
Nikita Mehrotra, Navdha Agarwal, Piyush Gupta +3
Code clones are duplicate code fragments that share (nearly) similar syntax or semantics. Code clone detection plays an important role in software maintenance, code refactoring, an…
JCoffee: Using Compiler Feedback to Make Partial Code Snippets Compilable
Piyush Gupta, Nikita Mehrotra, Rahul Purandare
Static program analysis tools are often required to work with only a small part of a program's source code, either due to the unavailability of the entire program or the lack of ne…
MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance
Anubha Kabra, Ayush Chopra, Nikaash Puri +4
Training a classification model on a dataset where the instances of one class outnumber those of the other class is a challenging problem. Such imbalanced datasets are standard in…
Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks
Surgan Jandial, Ayush Chopra, Mausoom Sarkar +3
Deep neural networks (DNNs) are powerful learning machines that have enabled breakthroughs in several domains. In this work, we introduce a new retrospective loss to improve the tr…
ShapeVis: High-dimensional Data Visualization at Scale
Nupur Kumari, Siddarth R., Akash Rupela +2
We present ShapeVis, a scalable visualization technique for point cloud data inspired from topological data analysis. Our method captures the underlying geometric and topological s…