35 citations · 135 across the 19 of their papers we have counts for
19 papers
Unveiling the Glass Veil: Elucidating the Optical Properties in Glasses with Interpretable Machine Learning
Mohd Zaki, Vineeth Venugopal, R. Ravinder +5
Due to their excellent optical properties, glasses are used for various applications ranging from smartphone screens to telescopes. Developing compositions with tailored Abbe numbe…
Twin Augmented Architectures for Robust Classification of COVID-19 Chest X-Ray Images
Kartikeya Badola, Sameer Ambekar, Himanshu Pant +5
The gold standard for COVID-19 is RT-PCR, testing facilities for which are limited and not always optimally distributed. Test results are delayed, which impacts treatment. Expert r…
Complexity Controlled Generative Adversarial Networks
Himanshu Pant, Jayadeva, Sumit Soman
One of the issues faced in training Generative Adversarial Nets (GANs) and their variants is the problem of mode collapse, wherein the training stability in terms of the generative…
Deep Learning Aided Rational Design of Oxide Glasses
R. Ravinder, Karthikeya H. Sreedhara, Suresh Bishnoi +5
Despite the extensive usage of oxide glasses for a few millennia, the composition-property relationships in these materials still remain poorly understood. While empirical and phys…
Guided Random Forest and its application to data approximation
Prashant Gupta, Aashi Jindal, Jayadeva +1
We present a new way of constructing an ensemble classifier, named the Guided Random Forest (GRAF) in the sequel. GRAF extends the idea of building oblique decision trees with loca…
Smaller Models, Better Generalization
Mayank Sharma, Suraj Tripathi, Abhimanyu Dubey +3
Reducing network complexity has been a major research focus in recent years with the advent of mobile technology. Convolutional Neural Networks that perform various vision tasks wi…