Python Binary-stochastic-neurons Resources

Deep Halftoning with Reversible Binary Pattern ICCV Paper | Project Website | BibTex Overview Existing halftoning algorithms usually drop colors and f

StochFuzz: A New Solution for Binary-only Fuzzing StochFuzz is a (probabilistically) sound and cost-effective fuzzing technique for stripped binaries.

E9AFL --- Binary AFL E9AFL inserts American Fuzzy Lop (AFL) instrumentation into x86_64 Linux binaries. This allows binaries to be fuzzed without the

QSYM: A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing Environment Tested on Ubuntu 14.04 64bit and 16.04 64bit Installation # disabl

About Fuzzification Fuzzification helps developers protect the released, binary-only software from attackers who are capable of applying state-of-the-

AntiFuzz: Impeding Fuzzing Audits of Binary Executables Get the paper here: https://www.usenix.org/system/files/sec19-guler.pdf Usage: The python scri

ON-LSTM This repository contains the code used for word-level language model and unsupervised parsing experiments in Ordered Neurons: Integrating Tree

IDA2Obj IDA2Obj is a tool to implement SBI (Static Binary Instrumentation). The working flow is simple: Dump object files (COFF) directly from one exe

TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

Awesome angr A collection of resources/tools and analyses for the angr binary analysis framework. This page does not only collect links and external r

Task-based End-to-end Model Learning in Stochastic Optimization This repository is by Priya L. Donti, Brandon Amos, and J. Zico Kolter and contains th

Modularized exploit generation framework for x86_64 binaries Overview This project is still at early stage of development, so you might want to come b

fourier-bayesian-sv-estimation Fourier-Bayesian estimation of stochastic volatility models Code used to run the numerical examples of "Bayesian Approa

ktool Static Mach-O binary metadata analysis tool / information dumper pip3 install k2l Development is currently taking place on the @python3.10 branc

Stochastic CSLR This is the PyTorch implementation for the ECCV 2020 paper: Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuou

hex2array-c Creates a C array from a hex-string. Usage Usage: python3 hex2array_c.py HEX_STRING [-h|--help] Use '-' to read the hex string from STDIN.

SDEdit: Image Synthesis and Editing with Stochastic Differential Equations Project | Paper | Colab PyTorch implementation of SDEdit: Image Synthesis a

knowledge-neurons An open source repository replicating the 2021 paper Knowledge Neurons in Pretrained Transformers by Dai et al., and extending the t

knowledge-neurons An open source repository replicating the 2021 paper Knowledge Neurons in Pretrained Transformers by Dai et al., and extending the t

Binary Stochastic Neurons in PyTorch http://r2rt.com/binary-stochastic-neurons-in-tensorflow.html https://github.com/pytorch/examples/tree/master/mnis

Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks (SDPoint) This repository contains the cod

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis Andreas Bl

Neuron Merging: Compensating for Pruned Neurons Pytorch implementation of Neuron Merging: Compensating for Pruned Neurons, accepted at 34th Conference

An implementation of a floating-point binary fractions class and module in Python. Work with binary fractions and binary floats with ease!

On the model-based stochastic value gradient for continuous reinforcement learning This repository is by Brandon Amos, Samuel Stanton, Denis Yarats, a

PMatch Semantic-based Patch Detection for Binary Programs Requirement tensorflow-gpu 1.13.1 numpy 1.16.2 scikit-learn 0.20.3 ssdeep 3.4 Usage tar -xvz

You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient (paper) @misc{zhang2021compress,

DeepLM DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition (CVPR 2021) Run Please install th

Midas ELF64 Injector Description Midas ELF64 Injector is a tool that will help you inject a C program from source code into an ELF64 binary. All you n

MNIST-dataset-extractor Extract MNIST handwritten digits dataset binary file into bmp images More info at http://yann.lecun.com/exdb/mnist/ Dependenci

BPR Binary Passage Retriever (BPR) is an efficient neural retrieval model for open-domain question answering. BPR integrates a learning-to-hash techni

Stochastic Image-to-Video Synthesis using cINNs Official PyTorch implementation of Stochastic Image-to-Video Synthesis using cINNs accepted to CVPR202

CasRel-pytorch-reimplement Pytorch reimplement of the paper "A Novel Cascade Binary Tagging Framework for Relational Triple Extraction" ACL2020. The o

Stochastic Normalizing Flows We introduce stochasticity in Boltzmann-generating flows. Normalizing flows are exact-probability generative models that

BNN - BN = ? Training Binary Neural Networks without Batch Normalization Codes for this paper BNN - BN = ? Training Binary Neural Networks without Bat

Vector Neurons: A General Framework for SO(3)-Equivariant Networks Created by Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacc

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks. Bayesian-Torch is designed to be flexible and seamless in extending a deterministic deep neural network architecture to corresponding Bayesian form by simply replacing the deterministic layers with Bayesian layers.

SABnzbd is an Open Source Binary Newsreader written in Python.

Website | Documentation (release) | Documentation (develop) | Glossary Table of Contents What does GPflow do? Installation Getting Started with GPflow

PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie

torch-optimizer torch-optimizer -- collection of optimizers for PyTorch compatible with optim module. Simple example import torch_optimizer as optim

Infinitely Deep Bayesian Neural Networks with SDEs This library contains JAX and Pytorch implementations of neural ODEs and Bayesian layers for stocha

BiPointNet: Binary Neural Network for Point Clouds Created by Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Li

Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not

nptsne nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation and HSNE modelling. For more detail s

Storchastic is a PyTorch library for stochastic gradient estimation in Deep Learning

A neural-based binary analysis tool Introduction This directory contains the demo of a neural-based binary analysis tool. We test the framework using

Score-Based Generative Modeling through Stochastic Differential Equations This repo contains the official implementation for the paper Score-Based Gen

nptsne nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation and HSNE modelling. For more detail s

wheel This library is the reference implementation of the Python wheel packaging standard, as defined in PEP 427. It has two different roles: A setupt

Conda is a cross-platform, language-agnostic binary package manager. It is the package manager used by Anaconda installations, but it may be used for

Neo4j Bolt Driver for Python This repository contains the official Neo4j driver for Python. Each driver release (from 4.0 upwards) is built specifical

Conda is a cross-platform, language-agnostic binary package manager. It is the package manager used by Anaconda installations, but it may be used for