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2 dépôts

Awesome GitHub RepositoriesFrequency Encodings

Transforms each input dimension into sine and cosine pairs at logarithmically spaced frequencies for neural network input.

Distinct from Input Encoding Combinations: Distinct from Input Encoding Combinations: focuses on the specific frequency-based encoding technique, not the combination of multiple encoding schemes.

Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Frequency Encodings. Refine with filters or upvote what's useful.

Awesome Frequency Encodings GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • fulldecent/system-bus-radioAvatar de fulldecent

    fulldecent/system-bus-radio

    6,680Voir sur GitHub↗

    System-bus-radio is a software-defined radio transmitter that generates AM radio signals by modulating the electromagnetic emissions from a computer's processor and memory bus, without requiring any dedicated radio hardware or physical antennas. It functions as a CPU electromagnetic emissions tool and processor-based signal generator, enabling radio transmission through precise control of CPU instructions and memory bus operations. The project encodes musical notes as sequences of frequency and duration pairs, then synthesizes the AM radio waveform in real-time by executing a tight loop of CP

    Encodes musical notes as frequency-duration pairs for playback via the modulated carrier.

    Cairgapcommunicationcommunication-protocol
    Voir sur GitHub↗6,680
  • nvlabs/tiny-cuda-nnAvatar de NVlabs

    NVlabs/tiny-cuda-nn

    4,418Voir sur GitHub↗

    This project is a high-performance C++ and CUDA neural network library designed for fast training and inference of small networks on NVIDIA GPUs. It serves as a specialized backend for neural radiance fields and coordinate-based networks, providing a fused GPU kernel library and a hash grid encoder for transforming raw input dimensions into high-dimensional representations. The library distinguishes itself through the use of C++ template metaprogramming and fused-kernel execution, which merge neural network layers into single GPU device functions to eliminate memory bottlenecks. It leverages

    Transforms each input dimension into sine and cosine pairs at logarithmically spaced frequencies.

    C++cudadeep-learninggpu
    Voir sur GitHub↗4,418
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Explorer les sous-tags

  • Musical Note EncodingsEncodes musical notes as sequences of frequency and duration pairs for playback via a modulated carrier. **Distinct from Frequency Encodings:** Distinct from Frequency Encodings: focuses on encoding musical notes for playback, not transforming input dimensions for neural networks.