53 citations · 89 across the 4 of their papers we have counts for
4 papers
Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges
Badri Narayana Patro, Vijay Srinivas Agneeswaran
Sequence modeling is a crucial area across various domains, including Natural Language Processing (NLP), speech recognition, time series forecasting, music generation, and bioinfor…
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…
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…