boleejia

boleejia

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awesome-bayesian-deep-learning

A curated list of resources dedicated to bayesian deep learning

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BayesianLearning

Bayesian Machine Learning

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BPL

Bayesian Program Learning model for one-shot learning

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caffe

Caffe for Structurally Sparse Deep Neural Networks

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Caffe_Code_Analysis

Caffe_Code_Analysis

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CNN-Accelerator-VLSI

Convolutional accelerator kernel, target ASIC & FPGA

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CNN-FPGA

Implementation of CNN on ZYNQ FPGA to classify handwritten numbers using MNIST database

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cnn_hardware_acclerator_for_fpga

This is a fully parameterized verilog implementation of computation kernels for accleration of the Inference of Convolutional Neural Networks on FPGAs

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cs231n.github.io

Public facing notes page

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DNN_NeuroSim_V2.0

Benchmark framework of compute-in-memory based accelerators for deep neural network

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edward

A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.

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LeetCode

The answer of LeetCode

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Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

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FPGAandCNN

基于FPGA的数字识别-实时视频处理的定点卷积神经网络实现

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Hardware_MLP_Verilog_CAD

MLP Hardware Implementation - Computer Aided Design Course - University of Tehran - Dr. Modarresi

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hdl

HDL libraries and projects

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ml-visuals

🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

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MLP-Verilog

Multi-layered perceptron neural network implemented in verilog.

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NTHU-ICLAB

清華大學 | 積體電路設計實驗 (IC LAB) | 110上

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PyDataLondon2017

Bayesian Deep Learning with Edward (and a trick using Dropout)

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pymc

PyMC: Bayesian Stochastic Modelling in Python (for PyMC3: https://github.com/pymc-devs/pymc3)

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scsynth

Synthesis tool for stochastic computing

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ST3_with_cpp

This Repo describes the method of compiling and running cpp file in sublime text 3

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