20 citations · 22 across the 3 of their papers we have counts for
4 papers
Deep Generative Models that Solve PDEs: Distributed Computing for Training Large Data-Free Models
Sergio Botelho, Ameya Joshi, Biswajit Khara +4
Recent progress in scientific machine learning (SciML) has opened up the possibility of training novel neural network architectures that solve complex partial differential equation…
ESPN: Extremely Sparse Pruned Networks
Minsu Cho, Ameya Joshi, Chinmay Hegde
Deep neural networks are often highly overparameterized, prohibiting their use in compute-limited systems. However, a line of recent works has shown that the size of deep networks…
Encoding Invariances in Deep Generative Models
Viraj Shah, Ameya Joshi, Sambuddha Ghosal +4
Reliable training of generative adversarial networks (GANs) typically require massive datasets in order to model complicated distributions. However, in several applications, traini…
Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers
Ameya Joshi, Amitangshu Mukherjee, Soumik Sarkar +1
Deep neural networks have been shown to exhibit an intriguing vulnerability to adversarial input images corrupted with imperceptible perturbations. However, the majority of adversa…