9 citations · 18 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
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…
Effect of Various Regularizers on Model Complexities of Neural Networks in Presence of Input Noise
Mayank Sharma, Aayush Yadav, Sumit Soman +1
Deep neural networks are over-parameterized, which implies that the number of parameters are much larger than the number of samples used to train the network. Even in such a regime…
Radius-margin bounds for deep neural networks
Mayank Sharma, Jayadeva, Sumit Soman
Explaining the unreasonable effectiveness of deep learning has eluded researchers around the globe. Various authors have described multiple metrics to evaluate the capacity of deep…