Advancing mathematics by guiding human intuition with AI

Overview

Advancing mathematics by guiding human intuition with AI

This repo contains two colab notebooks which accompany the paper, available online at https://www.nature.com/articles/s41586-021-04086-x

Both the representation theory and knot theory colabs retrain an ML model from scratch and recreate our published results by our same intermediary steps.

Installation

No installation is required; the notebook files can be opened on the Colab site from a copy of these files uploaded from a local machine, saved in google drive or directly from this github repo. Alternatively they can be accessed via these links:

Usage

Once the notebook has loaded, simply follow the comments along and execute all of the cells from top to bottom.

Citing this work

Please cite https://www.nature.com/articles/s41586-021-04086-x

Disclaimer

This is not an official Google product.

Data

Pre-trained weights and all data are licensed under licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

Owner
DeepMind
DeepMind
Python scripts using the Mediapipe models for Halloween.

Mediapipe-Halloween-Examples Python scripts using the Mediapipe models for Halloween. WHY Mainly for fun. But this repository also includes useful exa

Ibai Gorordo 23 Jan 06, 2023
Simulation of moving particles under microscopic imaging

Simulation of moving particles under microscopic imaging Install scipy numpy scikit-image tiffile Run python simulation.py Read result https://imagej

Zehao Wang 2 Dec 14, 2021
Code and project page for ICCV 2021 paper "DisUnknown: Distilling Unknown Factors for Disentanglement Learning"

DisUnknown: Distilling Unknown Factors for Disentanglement Learning See introduction on our project page Requirements PyTorch = 1.8.0 torch.linalg.ei

Sitao Xiang 24 May 16, 2022
pytorchのスライス代入操作をonnxに変換する際にScatterNDならないようにするサンプル

pytorch_remove_ScatterND pytorchのスライス代入操作をonnxに変換する際にScatterNDならないようにするサンプル。 スライスしたtensorにそのまま代入してしまうとScatterNDになるため、計算結果をcatで新しいtensorにする。 python ver

2 Dec 01, 2022
Automatically download the cwru data set, and then divide it into training data set and test data set

Automatically download the cwru data set, and then divide it into training data set and test data set.自动下载cwru数据集,然后分训练数据集和测试数据集

6 Jun 27, 2022
Hack Camera, Microphone, Location, Clipboard With Just a Link. Also, Get Many Details About Victim's Device. And So On...

An Automated Tool to Hack Victim's Camera, Microphone, Location, Clipboard. Has 2 Extra Features. Version 1.1 Update Fixed Some Major Bugs Data Saving

ToxicNoob 36 Jan 07, 2023
Implementation of the master's thesis "Temporal copying and local hallucination for video inpainting".

Temporal copying and local hallucination for video inpainting This repository contains the implementation of my master's thesis "Temporal copying and

David Álvarez de la Torre 1 Dec 02, 2022
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)

PointCNN: Convolution On X-Transformed Points Created by Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen. Introduction PointCNN

Yangyan Li 1.3k Dec 21, 2022
Like ThreeJS but for Python and based on wgpu

pygfx A render engine, inspired by ThreeJS, but for Python and targeting Vulkan/Metal/DX12 (via wgpu). Introduction This is a Python render engine bui

139 Jan 07, 2023
Official implementation of "Generating 3D Molecules for Target Protein Binding"

Generating 3D Molecules for Target Protein Binding This is the official implementation of the GraphBP method proposed in the following paper. Meng Liu

DIVE Lab, Texas A&M University 74 Dec 07, 2022
Off-policy continuous control in PyTorch, with RDPG, RTD3 & RSAC

arXiv technical report soon available. we are updating the readme to be as comprehensive as possible Please ask any questions in Issues, thanks. Intro

Zhihan 31 Dec 30, 2022
Task-related Saliency Network For Few-shot learning

Task-related Saliency Network For Few-shot learning This is an official implementation in Tensorflow of TRSN. Abstract An essential cue of human wisdo

1 Nov 18, 2021
NeRF Meta-Learning with PyTorch

NeRF Meta Learning With PyTorch nerf-meta is a PyTorch re-implementation of NeRF experiments from the paper "Learned Initializations for Optimizing Co

Sanowar Raihan 78 Dec 18, 2022
OneFlow is a performance-centered and open-source deep learning framework.

OneFlow OneFlow is a performance-centered and open-source deep learning framework. Latest News Version 0.5.0 is out! First class support for eager exe

OneFlow 4.2k Jan 07, 2023
Repo for flood prediction using LSTMs and HAND

Abstract Every year, floods cause billions of dollars’ worth of damages to life, crops, and property. With a proper early flood warning system in plac

1 Oct 27, 2021
Simulator for FRC 2022 challenge: Rapid React

rrsim Simulator for FRC 2022 challenge: Rapid React out-1.mp4 Usage In order to run the simulator use the following: python3 rrsim.py [config_path] wh

1 Jan 18, 2022
Pytorch implementation for "Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion" (NeurIPS 2021)

Density-aware Chamfer Distance This repository contains the official PyTorch implementation of our paper: Density-aware Chamfer Distance as a Comprehe

Tong WU 93 Dec 15, 2022
Python wrapper class for OpenVINO Model Server. User can submit inference request to OVMS with just a few lines of code

Python wrapper class for OpenVINO Model Server. User can submit inference request to OVMS with just a few lines of code.

Yasunori Shimura 7 Jul 27, 2022
Explainability for Vision Transformers (in PyTorch)

Explainability for Vision Transformers (in PyTorch) This repository implements methods for explainability in Vision Transformers

Jacob Gildenblat 442 Jan 04, 2023
A repo for Causal Imitation Learning under Temporally Correlated Noise

CausIL A repo for Causal Imitation Learning under Temporally Correlated Noise. Running Experiments To re-train an expert, run: python experts/train_ex

Gokul Swamy 5 Nov 01, 2022