patriciogonzalezvivo

Please consider using http://lygia.xyz instead of copy/pasting this functions. It expand suport for voronoi, voronoise, fbm, noise, worley, noise, derivatives and much more, through simple file dependencies. Take a look to https://github.com/patriciogonzalezvivo/lygia/tree/main/generative

Generic 1,2,3 Noise

float rand(float n){return fract(sin(n) * 43758.5453123);}

float noise(float p){
	float fl = floor(p);
  float fc = fract(p);

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

DanielKeep

HIT_HMD2043

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                                ||==|| I T
                               _||  ||_

                    Harold Innovation Technologies
                "If it ain't a HIT, it's a piece of..."

rygorous

// float->half variants.
// by Fabian "ryg" Giesen.
//
// I hereby place this code in the public domain, as per the terms of the
// CC0 license:
//
//   https://creativecommons.org/publicdomain/zero/1.0/
//
// float_to_half_full: This is basically the ISPC stdlib code, except
// I preserve the sign of NaNs (any good reason not to?)

adaugherity

#!/usr/bin/ruby
# Create display override file to force Mac OS X to use RGB mode for Display
# see http://embdev.net/topic/284710

require 'base64'

data=`ioreg -l -d0 -w 0 -r -c AppleDisplay`

edids=data.scan(/IODisplayEDID.*?<([a-z0-9]+)>/i).flatten
vendorids=data.scan(/DisplayVendorID.*?([0-9]+)/i).flatten

rygorous

// half->float variants.
// by Fabian "ryg" Giesen.
//
// I hereby place this code in the public domain.
// 
// half_to_float_fast: table based
// tables could be done in a more compact fashion (in particular, can store tab2 in low word of tab1!)
// but something of a dead end since not very SIMD-friendly. pretty much abandoned at this point.
//
// half_to_float_fast2: use FP adder hardware to deal with denormals.

yomotsu

var collision = {};


// aabb: <THREE.Box3>
// Plane: <THREE.Plane>
collision.isIntersectionAABBPlane = function ( aabb, Plane ) {

  var center = new THREE.Vector3().addVectors( aabb.max, aabb.min ).multiplyScalar( 0.5 ),
      extents = new THREE.Vector3().subVectors( aabb.max, center );

shagunsodhani

Key-Value Memory Networks for Directly Reading Documents

Introduction

• Knowledge Bases (KBs) are effective tools for Question Answering (QA) but are often too restrictive (due to fixed schema) and too sparse (due to limitations of Information Extraction (IE) systems).
• The paper proposes Key-Value Memory Networks, a neural network architecture based on Memory Networks that can leverage both KBs and raw data for QA.
• The paper also introduces MOVIEQA, a new QA dataset that can be answered by a perfect KB, by Wikipedia pages and by an imperfect KB obtained using IE techniques thereby allowing a comparison between systems using any of the three sources.
• Link to the paper.

Related Work

alertedsnake

# setup python virtualenv and install nodeenv
virtualenv .python
. .python/bin/activate
pip install nodeenv

# setup nodeenv with the node of your choice, and upgrade npm to latest
nodeenv --node=0.10.37 --prebuilt .node
. .node/bin/activate
npm install -g npm

kylemcdonald