3 citations · 7 across the 15 of their papers we have counts for
7 papers · 1 filter
k* Distribution: Evaluating the Latent Space of Deep Neural Networks using Local Neighborhood Analysis
Shashank Kotyan, Tatsuya Ueda, Danilo Vasconcellos Vargas
Most examinations of neural networks' learned latent spaces typically employ dimensionality reduction techniques such as t-SNE or UMAP. These methods distort the local neighborhood…
Synthetic Shifts to Initial Seed Vector Exposes the Brittle Nature of Latent-Based Diffusion Models
Mao Po-Yuan, Shashank Kotyan, Tham Yik Foong +1
Recent advances in Conditional Diffusion Models have led to substantial capabilities in various domains. However, understanding the impact of variations in the initial seed vector…
The Challenges of Image Generation Models in Generating Multi-Component Images
Tham Yik Foong, Shashank Kotyan, Po Yuan Mao +1
Recent advances in text-to-image generators have led to substantial capabilities in image generation. However, the complexity of prompts acts as a bottleneck in the quality of imag…
Towards Improving Robustness Against Common Corruptions using Mixture of Class Specific Experts
Shashank Kotyan, Danilo Vasconcellos Vargas
Neural networks have demonstrated significant accuracy across various domains, yet their vulnerability to subtle input alterations remains a persistent challenge. Conventional meth…
Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning
Shashank Kotyan, Danilo Vasconcellos Vargas
Neural networks have revolutionized various domains, exhibiting remarkable accuracy in tasks like natural language processing and computer vision. However, their vulnerability to s…
Improving Robustness for Vision Transformer with a Simple Dynamic Scanning Augmentation
Shashank Kotyan, Danilo Vasconcellos Vargas
Vision Transformer (ViT) has demonstrated promising performance in computer vision tasks, comparable to state-of-the-art neural networks. Yet, this new type of deep neural network…