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d-becking/README.md

Welcome to my GitHub!

Here, you’ll find some of my projects on:

  • 🔬 Neural Network Compression (NNC)
    Preprocessing (parameter / precision reduction), encoding, decoding, and transmission

  • 🔢 Quantization- and Explainability-Aware NN Training
    Using XAI and information theory within quantization-aware training to build efficient 2-4 bit neural networks

  • 📑 Research Papers, Challenges, and Demos
    Direct links to code, resources, and contributions

  • 🔜 Future work

    • Extensions for transformer-based models
    • Neural codecs and general-purpose compressors with language models

Research Interests

I've long been fascinated by neurophysiological processes and stimulus processing in the human brain. Translating these concepts into artificial neurons and synapses, alongside foundational information theory principles, forms a research area that continues inspiring me.

Personal Projects

Beyond my work, you might find tools related to my record collection 💽, playlist organization 📻, and synthesizers 🎹.

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  1. fraunhoferhhi/nncodec fraunhoferhhi/nncodec Public

    Fraunhofer Neural Network Encoder/Decoder (NNCodec)

    Python 70 5

  2. neurips-2019-micronet-challenge neurips-2019-micronet-challenge Public

    NeurIPS 2019 MicroNet Challenge

    Python 6 1

  3. ECQx ECQx Public

    ECQx: Explainability-Driven Quantization for Low-Bit and Sparse DNNs

    Python 1

  4. nncodec-icml-2023-demo nncodec-icml-2023-demo Public

    This repository is for reproducing the results shown in the NNCodec ICML Workshop paper. Additionally, it includes a demo, prepared for the Neural Compression Workshop (NCW).

    Python 1

  5. efficientCNNs efficientCNNs Public

    Finding Storage- and Compute-Efficient Convolutional Neural Networks

    Python 7 3