collaborators

5 papers

cs.LG2026

Robust Representation Learning in Masked Autoencoders

Anika Shrivastava, Renu Rameshan, Samar Agnihotri

Masked Autoencoders (MAEs) achieve impressive performance in image classification tasks, yet the internal representations they learn remain less understood. This work started as an…

cs.NI2026

Adaptive Local Combining with Decentralized Decoding for Distributed Massive MIMO

Mohd Saif Ali Khan, Karthik RM, Samar Agnihotri

Efficient uplink processing in distributed massive multiple-input multiple-output (D-mMIMO) systems requires both effective local combining and scalable decoding to significantly m…

cs.NI2026

Energy-and Spectral-Efficiency Trade-off in Distributed Massive-MIMO Networks

Mohd Saif Ali Khan, Karthik RM, Samar Agnihotri

This paper investigates the energy efficiency (EE) and spectral efficiency (SE) trade-off in uplink distributed massive multiple-input multiple-output (D-mMIMO) systems. Unlike con…

cs.NI2025

Pilot Assignment for Distributed Massive MIMO Based on Channel Estimation Error Minimization

Mohd Saif Ali Khan, Karthik RM, Samar Agnihotri

Pilot contamination remains a major bottleneck in realizing the full potential of distributed massive MIMO systems. We propose two dynamic and scalable pilot assignment schemes des…

cs.LG2025

Latent Space Characterization of Autoencoder Variants

Anika Shrivastava, Renu Rameshan, Samar Agnihotri

Understanding the latent spaces learned by deep learning models is crucial in exploring how they represent and generate complex data. Autoencoders (AEs) have played a key role in t…