69 Repositories
Python differential-enriched-loops Libraries
Flow control is the order in which statements or blocks of code are executed at runtime based on a condition. Learn Conditional statements, Iterative statements, and Transfer statements
03_Python_Flow_Control Introduction 👋 The control flow statements are an essential part of the Python programming language. A control flow statement
Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds."
DeltaConv [Paper] [Project page] Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds" by Ru
Reproduces the results of the paper "Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations".
Finite basis physics-informed neural networks (FBPINNs) This repository reproduces the results of the paper Finite Basis Physics-Informed Neural Netwo
Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )
Differential Privacy (DP) Based Federated Learning (FL) Everything about DP-based FL you need is here. (所有你需要的DP-based FL的信息都在这里) Code Tip: the code o
High-Resolution Differential Z-Belt Mod for V0 (with optional Kirigami support)
V0-DBM This is a high-resolution differential pulley system belt mod for the Z-axis on Voron 0 with optional Kirigami Bed support. NOTE: Alpha version
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable.
Diffrax Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. Diffrax is a JAX-based library providing numerical differe
Code for the tech report Toward Training at ImageNet Scale with Differential Privacy
Differentially private Imagenet training Code for the tech report Toward Training at ImageNet Scale with Differential Privacy by Alexey Kurakin, Steve
Create Arrays (Working with For Loops)
DSA with Python Create Arrays (Working with For Loops) CREATING ARRAYS WITH USER INPUT Array is a collection of items stored at contiguous memory loca
Deeplearning project at The Technological University of Denmark (DTU) about Neural ODEs for finding dynamics in ordinary differential equations and real world time series data
Authors Marcus Lenler Garsdal, [email protected] Valdemar Søgaard, [email protected] Simon Moe Sørensen, [email protected] Introduction This repo contains the
Finite Element Analysis
FElupe - Finite Element Analysis FElupe is a Python 3.6+ finite element analysis package focussing on the formulation and numerical solution of nonlin
BART aids transcribe tasks by taking a source audio file and creating automatic repeated loops, allowing transcribers to listen to fragments multiple times
BART (Beyond Audio Replay Technology) aids transcribe tasks by taking a source audio file and creating automatic repeated loops, allowing transcribers to listen to fragments multiple times (with possible overlap between segments).
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet
One Pixel Attack How simple is it to cause a deep neural network to misclassify an image if an attacker is only allowed to modify the color of one pix
An easy python calculator for those who want's to know how if statements, loops, and imports works give it a try!
A usefull calculator for any student or anyone who want's to know how to build a simple 2 mode python based calculator.
Parameter-ensemble-differential-evolution - Shows how to do parameter ensembling using differential evolution.
Ensembling parameters with differential evolution This repository shows how to ensemble parameters of two trained neural networks using differential e
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Finite difference solution of 2D Poisson equation. Can handle Dirichlet, Neumann and mixed boundary conditions.
Poisson-solver-2D Finite difference solution of 2D Poisson equation Current version can handle Dirichlet, Neumann, and mixed (combination of Dirichlet
Python library for ODE integration via Taylor's method and LLVM
heyoka.py Modern Taylor's method via just-in-time compilation Explore the docs » Report bug · Request feature · Discuss The heyókȟa [...] is a kind of
Visualizations of some specific solutions of different differential equations.
Diff_sims Visualizations of some specific solutions of different differential equations. Heat Equation in 1 Dimension (A very beautiful and elegant ex
Differential rendering based motion capture blender project.
TraceArmature Summary TraceArmature is currently a set of python scripts that allow for high fidelity motion capture through the use of AI pose estima
Training PyTorch models with differential privacy
Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the cli
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
PyDEns PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks. With PyDEns one can solve PD
Physics-Informed Neural Networks (PINN) and Deep BSDE Solvers of Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
NeuralPDE NeuralPDE.jl is a solver package which consists of neural network solvers for partial differential equations using scientific machine learni
Python framework for Stochastic Differential Equations modeling
SDElearn: a Python package for SDE modeling This package implements functionalities for working with Stochastic Differential Equations models (SDEs fo
Multiwavelets-based operator model
Multiwavelet model for Operator maps Gaurav Gupta, Xiongye Xiao, and Paul Bogdan Multiwavelet-based Operator Learning for Differential Equations In Ne
Simulation and Parameter Estimation in Geophysics
Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.
ScisorWiz: Differential Isoform Visualizer for Long-Read RNA Sequencing Data
ScisorWiz: Vizualizer for Differential Isoform Expression README ScisorWiz is a linux-based R-package for visualizing differential isoform expression
"Graph Neural Controlled Differential Equations for Traffic Forecasting", AAAI 2022
Graph Neural Controlled Differential Equations for Traffic Forecasting Setup Python environment for STG-NCDE Install python environment $ conda env cr
[NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators"
G-PATE This is the official code base for our NeurIPS 2021 paper: "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of T
Make differentially private training of transformers easy for everyone
private-transformers This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers. What is this? Why
This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression problems
Doctoral dissertation of Zheng Zhao This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression pro
PyTorch code for Composing Partial Differential Equations with Physics-Aware Neural Networks
FInite volume Neural Network (FINN) This repository contains the PyTorch code for models, training, and testing, and Python code for data generation t
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Score-Based Generative Modeling through Stochastic Differential Equations This repo contains a PyTorch implementation for the paper Score-Based Genera
Differential Privacy for Heterogeneous Federated Learning : Utility & Privacy tradeoffs
Differential Privacy for Heterogeneous Federated Learning : Utility & Privacy tradeoffs In this work, we propose an algorithm DP-SCAFFOLD(-warm), whic
Fit interpretable models. Explain blackbox machine learning.
InterpretML - Alpha Release In the beginning machines learned in darkness, and data scientists struggled in the void to explain them. Let there be lig
NDE: Climate Modeling with Neural Diffusion Equation, ICDM'21
Climate Modeling with Neural Diffusion Equation Introduction This is the repository of our accepted ICDM 2021 paper "Climate Modeling with Neural Diff
Physics-informed Neural Operator for Learning Partial Differential Equation
PINO Physics-informed Neural Operator for Learning Partial Differential Equation Abstract: Machine learning methods have recently shown promise in sol
Autonomous Ground Vehicle Navigation and Control Simulation Examples in Python
Autonomous Ground Vehicle Navigation and Control Simulation Examples in Python THIS PROJECT IS CURRENTLY A WORK IN PROGRESS AND THUS THIS REPOSITORY I
cLoops2: full stack analysis tool for chromatin interactions
cLoops2: full stack analysis tool for chromatin interactions Introduction cLoops2 is an extension of our previous work, cLoops. From loop-calling base
This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers.
private-transformers This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers. What is this? Why
A variant of LinUCB bandit algorithm with local differential privacy guarantee
Contents LDP LinUCB Description Model Architecture Dataset Environment Requirements Script Description Script and Sample Code Script Parameters Launch
Make OpenCV camera loops less of a chore by skipping the boilerplate and getting right to the interesting stuff
camloop Forget the boilerplate from OpenCV camera loops and get to coding the interesting stuff Table of Contents Usage Install Quickstart More advanc
Paper Code:A Self-adaptive Weighted Differential Evolution Approach for Large-scale Feature Selection
1. SaWDE.m is the main function 2. DataPartition.m is used to randomly partition the original data into training sets and test sets with a ratio of 7
Numerical methods for ordinary differential equations: Euler, Improved Euler, Runge-Kutta.
Numerical methods Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary
一个可以自动生成PTGen,MediaInfo,截图,并且生成发布所需内容的脚本
Differential 差速器 一个可以自动生成PTGen,MediaInfo,截图,并且生成发种所需内容的脚本 为什么叫差速器 差速器是汽车上的一种能使左、右轮胎以不同转速转动的结构。使用同样的动力输入,差速器能够输出不同的转速。就如同这个工具之于PT资源,差速器帮你使用同一份资源,输出不同PT
Deep learning library for solving differential equations and more
DeepXDE Voting on whether we should have a Slack channel for discussion. DeepXDE is a library for scientific machine learning. Use DeepXDE if you need
BioMASS - A Python Framework for Modeling and Analysis of Signaling Systems
Mathematical modeling is a powerful method for the analysis of complex biological systems. Although there are many researches devoted on produ
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations This repo contains official code for the NeurIPS 2021 paper Imi
DP-CL(Continual Learning with Differential Privacy)
DP-CL(Continual Learning with Differential Privacy) This is the official implementation of the Continual Learning with Differential Privacy. If you us
A python package to display progress of loops to the user
ProgressBars A python package to display progress of loops to the user. Installation This package can be installed using pip. pip install progressbars
Conveniently measures the time of your loops, contexts and functions.
Conveniently measures the time of your loops, contexts and functions.
Differential fuzzing for the masses!
NEZHA NEZHA is an efficient and domain-independent differential fuzzer developed at Columbia University. NEZHA exploits the behavioral asymmetries bet
HyDiff: Hybrid Differential Software Analysis
HyDiff: Hybrid Differential Software Analysis This repository provides the tool and the evaluation subjects for the paper HyDiff: Hybrid Differential
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
PhyCRNet Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs Paper link: [ArXiv] By: Pu Ren, Chengping Rao, Yang
[NeurIPS 2021] Galerkin Transformer: a linear attention without softmax
[NeurIPS 2021] Galerkin Transformer: linear attention without softmax Summary A non-numerical analyst oriented explanation on Toward Data Science abou
Leibniz is a python package which provide facilities to express learnable partial differential equations with PyTorch
Leibniz is a python package which provide facilities to express learnable partial differential equations with PyTorch
Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations
ODE GAN (Prototype) in PyTorch Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary
By default, networkx has problems with drawing self-loops in graphs.
By default, networkx has problems with drawing self-loops in graphs. It makes it hard to draw a graph with self-loops or to make a nicely looking chord diagram. This repository provides some code to draw self-loops nicely
PyTorch implementation for SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
SDEdit: Image Synthesis and Editing with Stochastic Differential Equations Project | Paper | Colab PyTorch implementation of SDEdit: Image Synthesis a
Bachelor's Thesis in Computer Science: Privacy-Preserving Federated Learning Applied to Decentralized Data
federated is the source code for the Bachelor's Thesis Privacy-Preserving Federated Learning Applied to Decentralized Data (Spring 2021, NTNU) Federat
This is our ARTS test set, an enriched test set to probe Aspect Robustness of ABSA.
This is the repository for our 2020 paper "Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis". Data We provide
Differentiable Optimizers with Perturbations in Pytorch
Differentiable Optimizers with Perturbations in PyTorch This contains a PyTorch implementation of Differentiable Optimizers with Perturbations in Tens
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
scikit-opt Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm,A
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie
higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.
higher is a library providing support for higher-order optimization, e.g. through unrolled first-order optimization loops, of "meta" aspects of these
Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561
Meta-Solver for Neural Ordinary Differential Equations Towards robust neural ODEs using parametrized solvers. Main idea Each Runge-Kutta (RK) solver w
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
Infinitely Deep Bayesian Neural Networks with SDEs This library contains JAX and Pytorch implementations of neural ODEs and Bayesian layers for stocha
Official code for Score-Based Generative Modeling through Stochastic Differential Equations
Score-Based Generative Modeling through Stochastic Differential Equations This repo contains the official implementation for the paper Score-Based Gen
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
scikit-opt Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm,A