1. Unit startpage
  2. Employees
  3. Rohit Agarwal
Bilde av Agarwal, Rohit
Bilde av Agarwal, Rohit
Institutt for informatikk rohit.agarwal@uit.no +4777646320 Tromsø You can find me here

Rohit Agarwal

  • Deepak Kumar Gupta, Udbhav Bamba, Abhishek Thakur, Akash Gupta, Rohit Agarwal, Suraj Sharan et al.:
    An UltraMNIST classification benchmark to train CNNs for very large images
    Scientific Data 2024 DOI / ARKIV
  • Rohit Agarwal, Ludwig Alexander Horsch, Krishna Agarwal, Dilip Kumar Prasad :
    Online Learning under Haphazard Input Conditions: A Comprehensive Review and Analysis
    arXiv 2024 DOI / ARKIV
  • Rohit Agarwal, Ludwig Alexander Horsch, Krishna Agarwal, Dilip Kumar Prasad :
    packetLSTM: Dynamic LSTM Framework for Streaming Data with Varying Feature Space
    arXiv 2024 DOI
  • Gauri Arora, Ankit Butola, Ruchi Rajput, Rohit Agarwal, Krishna Agarwal, Ludwig Alexander Horsch et al.:
    Taxonomy of hybridly polarized Stokes vortex beams
    Optics Express 2024 DOI / ARKIV
  • Himanshu Buckchash, Momojit Biswas, Rohit Agarwal, Dilip Kumar Prasad :
    Hedging Is Not All You Need: A Simple Baseline for Online Learning Under Haphazard Inputs
    arXiv 2024 DOI
  • Rohit Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Modelling Irregularly Sampled Time Series Without Imputation
    arXiv.org 2023 DOI
  • Rohit Agarwal, Ankit Butola, Ludwig Alexander Horsch, Dilip Kumar Prasad, Krishna Agarwal :
    Taxonomy of hybridly polarized Stokes vortex beams
    arXiv.org 2023 DOI
  • 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
  • Rohit Agarwal, Dilip K. Prasad :
    Scalable Online Deep Learning for Streaming Data with Variable Feature Spaces: Architectures, Imparting Scalability and Data Transformation
    UiT Norges arktiske universitet 12. novembre 2025
  • Rohit Agarwal :
    Haphazard Inputs: Handling Dimension Varying Inputs in an Online Setting
    2023
  • Rohit Agarwal :
    Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts
    2023
  • Rohit Agarwal :
    Haphazard Inputs: Handling Dimension Varying Inputs in an Online Setting
    2023
  • Rohit Agarwal :
    In-context Learning, Finetuning and RLHF in LLMs​
    2023
  • Rohit Agarwal, Krishna Agarwal, Alexander Horsch, Dilip K. Prasad :
    Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs
    2022 DOI / ARKIV

    • The 50 latest publications is shown on this page. See all publications in Cristin here →
    Realfagbygget A228


    Click for bigger map