Python Physics-benchmarking-neurips2021 Resources

Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme (NeurIPS2021) Overview Prerequisites Linux Pytho

Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking We revisit and address issues with Oxford 5k and Paris 6k image retrieval benchm

[Official] FINE Samples for Learning with Noisy Labels This repository is the official implementation of "FINE Samples for Learning with Noisy Labels"

Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization This codebase is the official implementation of Test-Time Classifier A

ElectriPy ⚡ Visualize the electric field of a point charges network. 🔌 Installation Install ElectriPy package: $ pip install electripy You are all d

Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation (NeurIPS 2021) Code for our NeurIPS 2021 paper 'Exploiting the Intri

DQC: Differentiable Quantum Chemistry Differentiable quantum chemistry package. Currently only support differentiable density functional theory (DFT)

Physion: Evaluating Physical Prediction from Vision in Humans and Machines This repo contains code and data to reproduce the results in our paper, Phy

Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Code for NeurIPS 2021 Paper "Exploring Architectural Ingredients of A

solar-system-pygame Controls UP/DOWN for Emulation Speed Control ESC for Pause/Unpause q to Quit c or ESC again to Continue LEFT CLICK to Add an orbit

dm_control: DeepMind Infrastructure for Physics-Based Simulation. DeepMind's software stack for physics-based simulation and Reinforcement Learning en

Diffusion Normalizing Flow (DiffFlow) Reproduce setup environment The repo heavily depends on jam, a personal toolbox developed by Qsh.zh. The API may

OOD Detection Load conda environment conda env create -f environment.yml or install requirements: while read requirement; do conda install --yes $requ

Multi-Objective Loss Balancing for Physics-Informed Deep Learning Code for ReLoBRaLo. Abstract Physics Informed Neural Networks (PINN) are algorithms

Learning to Learn Graph Topologies This is the official code of L2G, Unrolling and Recurrent Unrolling in Learning to Learn Graph Topologies. Requirem

MuJoCo Physics MuJoCo stands for Multi-Joint dynamics with Contact. It is a general purpose physics engine that aims to facilitate research and develo

Transferability for domain generalization This repo is for evaluating and improving transferability in domain generalization (NeurIPS 2021), based on

Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

ARES This repository contains the code for ARES (Adversarial Robustness Evaluation for Safety), a Python library for adversarial machine learning rese

Open-source library for reliable evaluation on reinforcement learning and machine learning benchmarks. See NeurIPS 2021 oral for details.

Time-Sensitive-QA The repo contains the dataset and code for NeurIPS2021 (dataset track) paper Time-Sensitive Question Answering dataset. The dataset

Deep Markov Factor Analysis (DMFA) Codes and experiments for deep Markov factor analysis (DMFA) model accepted for publication at NeurIPS2021: A. Farn

pySPEDAS pySPEDAS is an implementation of the SPEDAS framework for Python. The Space Physics Environment Data Analysis Software (SPEDAS) framework is

LeBenchmark: a reproducible framework for assessing SSL from speech

Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W

Benchmarking the robustness of Spatial-Temporal Models This repositery contains the code for the paper Benchmarking the Robustness of Spatial-Temporal

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W

LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh

Python-Orbit-Sim A 2D physics sim for orbits. Made using pygame and tkinter. High degree of intractability, allowing you to create celestial bodies of

ProFuzzBench - A Benchmark for Stateful Protocol Fuzzing ProFuzzBench is a benchmark for stateful fuzzing of network protocols. It includes a suite of

PhyCRNet Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs Paper link: [ArXiv] By: Pu Ren, Chengping Rao, Yang

PiSL A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery. Sun, F., Liu, Y. and Sun, H., 2021. Physics-informe

PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

The first comprehensive Robustness investigation benchmark on large-scale dataset ImageNet regarding ARchitecture design and Training techniques towards diverse noises.

Don’t be Contradicted with Anything!CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System This repository contains the PyTorch im

Merlion: A Machine Learning Library for Time Series Table of Contents Introduction Installation Documentation Getting Started Anomaly Detection Foreca

Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processing model outputs, and evaluating model performance. I

💻 Physics2Calculator A simple and powerful calculator for Physics 2 🔌 Predefined constants pi = 3.14159... k = 8988000000 (coulomb constant) e0 = 8.

PINNpapers Contributed by IDRL lab. Introduction Physics-Informed Neural Network (PINN) has achieved great success in scientific computing since 2017.

Zero-Shot Domain Adaptation with a Physics Prior [arXiv] [sup. material] - ICCV 2021 Oral paper, by Attila Lengyel, Sourav Garg, Michael Milford and J

CARLA - Counterfactual And Recourse Library CARLA is a python library to benchmark counterfactual explanation and recourse models. It comes out-of-the

Map Metrics for Trajectory Quality Map metrics toolkit provides a set of metrics to quantitatively evaluate trajectory quality via estimating consiste

zoofs is a Python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.

FedScale: Benchmarking Model and System Performance of Federated Learning (Paper) This repository contains scripts and instructions of building FedSca

Heterogeneous Graph Benchmark Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks. Roadmap We organize our repo by task, and on

Interaction-Network-Pytorch Pytorch Implementraion of Interaction Networks for Learning about Objects, Relations and Physics. Interaction Network is a

Visual-Interaction-Networks An implementation of Deepmind visual interaction networks in Pytorch. Introduction For the purpose of understanding the ch

IDRLnet IDRLnet is a machine learning library on top of PyTorch. Use IDRLnet if you need a machine learning library that solves both forward and inver

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).

Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics This repository is the official PyTorch implementation of "Physics-aware Differ

PyMedPhys is an open-source Medical Physics python library built by an open community that values and prioritises code sharing, review, improvement, and learning from each other. I

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).

PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Relighting and Material Editing CVPR 2021. Project page: https://kai-46.github.io/

whm also known as wifi-heat-mapper is a Python library for benchmarking Wi-Fi networks and gather useful metrics that can be converted into meaningful easy-to-understand heatmaps.

A toy project using OpenCV, PyMunk and Mediapipe the source code for my LindkedIn post It's just a toy project and I didn't write a documentation yet,

This repo includes the Pytorch-Geometric implementation of a series of Graph Neural Network (GNN) based fake news detection models. All GNN models are implemented and evaluated under the User Preference-aware Fake News Detection (UPFD) framework. The fake news detection problem is instantiated as a graph classification task under the UPFD framework.

Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation. It was introduced in Wright, Logan G. & Onodera, Tatsuhiro et al. (2021)1 to train Physical Neural Networks (PNNs) - neural networks whose building blocks are physical systems.

PyDy, short for Python Dynamics, is a tool kit written in the Python programming language that utilizes an array of scientific programs to enable the study of multibody dynamics. The goal is to have a modular framework and eventually a physics abstraction layer which utilizes a variety of backends that can provide the user with their desired workflow

FedNLP is a research-oriented benchmarking framework for advancing federated learning (FL) in natural language processing (NLP). It uses FedML repository as the git submodule. In other words, FedNLP only focuses on adavanced models and dataset, while FedML supports various federated optimizers (e.g., FedAvg) and platforms (Distributed Computing, IoT/Mobile, Standalone).

Table of contents What is PEM? Overview Installation Usage Executable Library Telegram Bot Try OPEM in Your Browser! MATLAB Issues & Bug Reports Contr

airspeed velocity airspeed velocity (asv) is a tool for benchmarking Python packages over their lifetime. It is primarily designed to benchmark a sing

Overview docs tests package A pytest fixture for benchmarking code. It will group the tests into rounds that are calibrated to the chosen timer. See c

Locust Locust is an easy to use, scriptable and scalable performance testing tool. You define the behaviour of your users in regular Python code, inst

Diffraction Simulations - Angular Spectrum Method Implementation of the Angular Spectrum method in Python to simulate Diffraction Patterns with arbitr

Locust Locust is an easy to use, scriptable and scalable performance testing tool. You define the behaviour of your users in regular Python code, inst

Locust Locust is an easy to use, scriptable and scalable performance testing tool. You define the behaviour of your users in regular Python code, inst