Ray tracing of a Schwarzschild black hole written entirely in TensorFlow.

Last update: Jan 15, 2022

Related tags

Deep Learning TensorGeodesic

Overview

TensorGeodesic

Ray tracing of a Schwarzschild black hole written entirely in TensorFlow.

Dependencies:

Python 3
TensorFlow 2.x
numpy
matplotlib

About

The Schwarzschild metric is currently implemented, with Christoffel symbols computed via automatic differentiation by tf.GradientTape.batch_jacobian. Geodesics from the observer are integrated using the classic fourth Runge-Kutta method (RK4).

Since the program is written in TensorFlow, it is fully differentiable and supports arbitrary CPU/GPU systems. In particular, it works on my M1 Max MacBook Pro.

Tested on TensorFlow 2.7.0, with Apple's tensorflow-metal 0.3.0 plugin (!!!)

Owner

GitHub Repository

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Ray tracing of a Schwarzschild black hole written entirely in TensorFlow.

Related tags

Overview

TensorGeodesic

Dependencies:

About

Owner

Liquid Warping GAN with Attention: A Unified Framework for Human Image Synthesis

Understanding Hyperdimensional Computing for Parallel Single-Pass Learning

This is a model to classify Vietnamese sign language using Motion history image (MHI) algorithm and CNN.

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A non-linear, non-parametric Machine Learning method capable of modeling complex datasets

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Source code of our BMVC 2021 paper: AniFormer: Data-driven 3D Animation with Transformer

Sequential model-based optimization with a `scipy.optimize` interface

Code for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.

Python package for covariance matrices manipulation and Biosignal classification with application in Brain Computer interface

Code-free deep segmentation for computational pathology

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