The HPC toolbox: fused matrix multiplication, convolution, data-parallel strided tensor primitives, OpenMP facilities, SIMD, JIT Assembler, CPU detection, state-of-the-art vectorized BLAS for float…

Tensors and Dynamic neural networks in Python with strong GPU acceleration

QONNX: Arbitrary-Precision Quantized Neural Networks in ONNX

深度学习经典、新论文逐段精读

Bi-Real Net: Enhancing the Performance of 1-bit CNNs With Improved Representational Capability and Advanced Training Algorithm. In ECCV 2018 and IJCV

Open source process design kit for usage with SkyWater Technology Foundry's 130nm node.

SKY130 ReRAM and examples (SkyWater Provided)

Sandbox for training deep learning networks

Vitis AI is Xilinx’s development stack for AI inference on Xilinx hardware platforms, including both edge devices and Alveo cards.

Installs Vivado on M1/M2/M3 macs

Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).

The code for "Short-term traffic flow prediction in bike sharing networks"

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

Latex code for making neural networks diagrams

PyTorch implementation for 3D CNN models for medical image data (1 channel gray scale images).

3D ResNets for Action Recognition (CVPR 2018)

Brevitas: neural network quantization in PyTorch

Binary complex neural network

Simple Training and Deployment of Fast End-to-End Binary Networks

Efficient computing methods developed by Huawei Noah's Ark Lab

Code for High-Capacity Expert Binary Networks (ICLR 2021).

ConvNet training using pytorch

Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

Jupyter notebook examples on image classification with quantized neural networks

What's Next? Next Frame Prediction with Deep Learning Approach

In this project we have explored the use of imaging time series to enhance forecasting results with Neural Networks. The approach has revealed itself to be extremely promising as, both in combinati…

Convolutional LSTM for ASKA Data

A model that predicts the future frame based on the movement of objects in the previous set of N frames.