REPRODUCIBLE RESEARCH

Code & implementations

Software and implementations connected to the center’s research.

8

From the research archive
Code

Regularization with Keras & TensorFlow

A regularization library by Mohammad Mahdi Bejani.

Full archive description
  • A simple and extensive library for regularization with Keras and Tensorflow, By Dr. Mohammad Mahdi Bejani, See Github Link here.
  • Code

    Laliga auxiliary loss functions

    Convolutional neural networks · Mohammad Mahdi Bejani.

    Full archive description
  • Least auxiliary loss-functions with impact growth adaptation (Laliga) for convolutional neural networks, By Dr. Mohammad Mahdi Bejani, See Github Link here.
  • Code

    Adaptive low-rank regularization

    Damping sequences for lazy weights in deep networks · Mohammad Mahdi Bejani.

    Full archive description
  • Adaptive Low-Rank Regularization with Damping Sequences to Restrict Lazy Weights in Deep Networks, By Dr. Mohammad Mahdi Bejani, See Github Link here.
  • Code

    Adaptive weight decay

    PyTorch implementation · Mohammad Mahdi Bejani.

    Full archive description
  • Adaptive Weight Decay Regularization based on Pytorch Framework, By Dr. Mohammad Mahdi Bejani, See Github Link here.
  • Code

    Deep-network regularization

    PyTorch framework · Mohammad Mahdi Bejani.

    Full archive description
  • Regularization of Deep Neural Networks based on Pytorch framework, By Dr. Mohammad Mahdi Bejani, See Github Link here.
  • Code

    Driver identification

    Implementation by Ruhallah Ahmadian.

    Full archive description
  • Driver-Identification, By Mr. Ruhallah Ahmadian, See Github Link here.
  • Code

    Styled & diverse image captioning

    Implementation by Marzi Heidari.

    Full archive description
  • Styled and Diverse Image Captioning, By Ms. Marzi Heidari, See Github Link here.
  • Code

    Data resources for intelligent transportation

    Research data resources linked from the NORC archive.

    Full archive description
  • Some Data Resources for Intelligent Transportation Systems, See Github Link here.