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Udbhav Bamba,
Abhishek Thakur,
Akash Gupta,
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Suraj Sharan
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An UltraMNIST classification benchmark to train CNNs for very large images
Rohit Agarwal,
Ludwig Alexander Horsch,
Krishna Agarwal,
Dilip Kumar Prasad
:
Online Learning under Haphazard Input Conditions: A Comprehensive Review and Analysis
Rohit Agarwal,
Ludwig Alexander Horsch,
Krishna Agarwal,
Dilip Kumar Prasad
:
packetLSTM: Dynamic LSTM Framework for Streaming Data with Varying Feature Space
Gauri Arora,
Ankit Butola,
Ruchi Rajput,
Rohit Agarwal,
Krishna Agarwal,
Ludwig Alexander Horsch
et al.:
Taxonomy of hybridly polarized Stokes vortex beams
Himanshu Buckchash,
Momojit Biswas,
Rohit Agarwal,
Dilip Kumar Prasad
:
Hedging Is Not All You Need: A Simple Baseline for Online Learning Under Haphazard Inputs
Rohit Agarwal,
Ludwig Alexander Horsch,
Dilip Kumar Prasad
:
Modelling Irregularly Sampled Time Series Without Imputation
Rohit Agarwal,
Ankit Butola,
Ludwig Alexander Horsch,
Dilip Kumar Prasad,
Krishna Agarwal
:
Taxonomy of hybridly polarized Stokes vortex beams
Rohit Agarwal,
Gyanendra Das,
Saksham Aggarwal,
Ludwig Alexander Horsch,
Dilip Kumar Prasad
:
Mabnet: Master Assistant Buddy Network With Hybrid Learning for Image Retrieval
Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2023
DOI /
ARKIV
Rohit Agarwal,
Dilip Kumar Prasad,
Ludwig Alexander Horsch,
Deepak Kumar Gupta
:
Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts
Transactions on Machine Learning Research (TMLR) 2023
ARKIV