Ramashish Gaurav

According to our database, Ramashish Gaurav authored at least 10 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Benchmarking Deep Legendre-SNN for Time Series Classification - Analysis and Enhancements.

Ramashish Gaurav, Shrestha Agarwal, Terrence C. Stewart, Yang Yi

IEEE Trans. Emerg. Top. Comput. Intell., February, 2026

Temporal Learning for Edge AI: Hyperdimensional Computing with Legendre Delay Networks.

Md. Rubel Sarkar, Ramashish Gaurav, Govind Sunil Kumar, Shirazush Salekin Chowdhury, Yang Yi

Proceedings of the International Conference on Computing, Networking and Communications, 2026

2025

DALTON - Deep Local Learning in SNNs via Local Weights and Surrogate-Derivative Transfer.

Ramashish Gaurav, Duy Anh Do, Thinh Thanh Doan, Yang Yi

IEEE Trans. Emerg. Top. Comput., 2025

2023

Reservoir based spiking models for univariate Time Series Classification.

Ramashish Gaurav, Terrence C. Stewart, Yang Yi

Frontiers Comput. Neurosci., February, 2023

2022

Spiking Approximations of the MaxPooling Operation in Deep SNNs.

Ramashish Gaurav, Bryan P. Tripp, Apurva Narayan

Proceedings of the International Joint Conference on Neural Networks, 2022

Spiking Reservoir Computing for Temporal Edge Intelligence on Loihi.

Ramashish Gaurav, Terrence C. Stewart, Yang Cindy Yi

Proceedings of the 7th IEEE/ACM Symposium on Edge Computing, 2022

2021

Driving Scene Understanding: How much temporal context and spatial resolution is necessary?

Ramashish Gaurav, Bryan P. Tripp, Apurva Narayan

Proceedings of the 34th Canadian Conference on Artificial Intelligence, 2021

2018

A Train Status Assistant for Indian Railways.

Himadri Mishra, Ramashish Gaurav, Biplav Srivastava

CoRR, 2018

Estimating Train Delays in a Large Rail Network Using a Zero Shot Markov Model.

Ramashish Gaurav, Biplav Srivastava

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

2016

Informed multimodal latent subspace learning via supervised matrix factorization.

Ramashish Gaurav, Mridula Verma, Kaushal Kumar Shukla

Proceedings of the Tenth Indian Conference on Computer Vision, 2016