53 citations · 92 across the 6 of their papers we have counts for
6 papers
SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series
Badri N. Patro, Vijay S. Agneeswaran
Transformers have widely adopted attention networks for sequence mixing and MLPs for channel mixing, playing a pivotal role in achieving breakthroughs across domains. However, rece…
Scattering Vision Transformer: Spectral Mixing Matters
Badri N. Patro, Vijay Srinivas Agneeswaran
Vision transformers have gained significant attention and achieved state-of-the-art performance in various computer vision tasks, including image classification, instance segmentat…
SpectFormer: Frequency and Attention is what you need in a Vision Transformer
Badri N. Patro, Vinay P. Namboodiri, Vijay Srinivas Agneeswaran
Vision transformers have been applied successfully for image recognition tasks. There have been either multi-headed self-attention based (ViT \cite{dosovitskiy2020image}, DeIT, \ci…
Efficiency 360: Efficient Vision Transformers
Badri N. Patro, Vijay Srinivas Agneeswaran
Transformers are widely used for solving tasks in natural language processing, computer vision, speech, and music domains. In this paper, we talk about the efficiency of transforme…
Detecting Concept Drift in the Presence of Sparsity -- A Case Study of Automated Change Risk Assessment System
Vishwas Choudhary, Binay Gupta, Anirban Chatterjee +3
Missing values, widely called as \textit{sparsity} in literature, is a common characteristic of many real-world datasets. Many imputation methods have been proposed to address this…
Look Before You Leap! Designing a Human-Centered AI System for Change Risk Assessment
Binay Gupta, Anirban Chatterjee, Harika Matha +3
Reducing the number of failures in a production system is one of the most challenging problems in technology driven industries, such as, the online retail industry. To address this…