activity
20192022
most citedBuilding Deep, Equivariant Capsule Networks

8 citations · 17 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

Iterative collaborative routing among equivariant capsules for transformation-robust capsule networks

Sai Raam Venkataraman, S. Balasubramanian, R. Raghunatha Sarma

Transformation-robustness is an important feature for machine learning models that perform image classification. Many methods aim to bestow this property to models by the use of da…

cs.CV20221 cited

Robustcaps: a transformation-robust capsule network for image classification

Sai Raam Venkataraman, S. Balasubramanian, R. Raghunatha Sarma

Geometric transformations of the training data as well as the test data present challenges to the use of deep neural networks to vision-based learning tasks. In order to address th…

cs.CV2022

Can you even tell left from right? Presenting a new challenge for VQA

Sai Raam Venkatraman, Rishi Rao, S. Balasubramanian +2

Visual Question Answering (VQA) needs a means of evaluating the strengths and weaknesses of models. One aspect of such an evaluation is the evaluation of compositional generalisati…

cs.LG20207 cited

Learning Compositional Structures for Deep Learning: Why Routing-by-agreement is Necessary

Sai Raam Venkatraman, Ankit Anand, S. Balasubramanian +1

A formal description of the compositionality of neural networks is associated directly with the formal grammar-structure of the objects it seeks to represent. This formal grammar-s…

cs.LG20198 cited

Building Deep, Equivariant Capsule Networks

Sairaam Venkatraman, S. Balasubramanian, R. Raghunatha Sarma

Capsule networks are constrained by the parameter-expensive nature of their layers, and the general lack of provable equivariance guarantees. We present a variation of capsule netw…