Rob Zinkov zaxtax

## EXAMPLE.service
[Unit]
Description=Description of this service

[Service]
Type=simple
ExecStart=/usr/bin/nohup /path/to/server.sh
Restart=always
RestartSec=30
StandardOutput=/path/to/log
StandardError=/path/to/log

## progress_bar_test.ipynb

      
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                zaxtax
                / progress_bar_test.ipynb
            
            
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              April 2, 2024 11:25
            
              
                Example notebook showing multiple chain progress bars for blackjax
              
          
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## ln_cass.py
# Implementation of the logit-normal continuous analogue of the spike-and-slab (LN-CASS) prior
# From https://royalsocietypublishing.org/doi/full/10.1098/rsif.2018.0572
import pymc as pm
import numpy as np
import matplotlib.pyplot as plt

mu = 0
tau = 5
sigma = 10
with pm.Model() as m:

## semantic_similarity.ipynb

      
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                zaxtax
                / semantic_similarity.ipynb
            
            
              Created
              October 20, 2022 04:56
                — forked from itsuncheng/semantic_similarity.ipynb
            
          
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## reading-list.rst

      
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                zaxtax
                / reading-list.rst
            
            
              Created
              December 19, 2021 23:44
                — forked from alexjc/reading-list.rst
            
              
                Reading List on Texture Synthesis
              
          
    Specific Papers


https://arxiv.org/abs/1505.07376
Texture Synthesis Using Convolutional Neural Networks


https://arxiv.org/abs/1508.06576
A Neural Algorithm of Artistic Style


https://arxiv.org/abs/1603.03417
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images


https://arxiv.org/abs/1701.02096
Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Texture Synthesis


## README.md

      
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                zaxtax
                / README.md
            
            
              Created
              March 1, 2021 23:27
                — forked from lmullen/README.md
            
              
                Getting the Ace editor to work with gitit
              
          
    The file page.st goes in the templates/ directory in the Gitit wiki home directory. You'll put the Ace JavaScript and CSS files in static/.

  
## wt.sh
#!/bin/sh

TT=`env TZ=Asia/Tokyo date`
ST=`env TZ=Asia/Singapore date`
BT=`env TZ=Europe/Berlin date`
LT=`env TZ=Europe/London date`
ET=`env TZ=America/New_York date`
PT=`env TZ=US/Pacific date`
HT=`env TZ=Pacific/Honolulu date`
DT=`env TZ=Etc/GMT+12 date`

## CPS.rkt
#lang racket

;;;; CPS translaions written with guidance from Ken Shan's notes
;;;; and Danvy & Filinkski's paper Abstracting Control

(define empty-env '())

(define (extend-env name value env)
  (cons (list name value) env))

## hist.py
#!/usr/bin/env python3

import click
import numpy as np
import sys


class IntOrStr(click.ParamType):
    name = 'int/str'

## Infer.hs
{-# LANGUAGE FlexibleInstances #-}

-- | An implementation of Section 3, Local Type Argument Synthesis, from the
-- paper /Local Type Inference/ by Pierce and Turner.
module Infer where

import Control.Monad (foldM, join, zipWithM)
import Data.Function (on)
import Data.List (foldl', groupBy, intercalate, intersect, nub)
	[Unit]
	Description=Description of this service

	[Service]
	Type=simple
	ExecStart=/usr/bin/nohup /path/to/server.sh
	Restart=always
	RestartSec=30
	StandardOutput=/path/to/log
	StandardError=/path/to/log
	# Implementation of the logit-normal continuous analogue of the spike-and-slab (LN-CASS) prior
	# From https://royalsocietypublishing.org/doi/full/10.1098/rsif.2018.0572
	import pymc as pm
	import numpy as np
	import matplotlib.pyplot as plt

	mu = 0
	tau = 5
	sigma = 10
	with pm.Model() as m:
	#!/bin/sh

	TT=`env TZ=Asia/Tokyo date`
	ST=`env TZ=Asia/Singapore date`
	BT=`env TZ=Europe/Berlin date`
	LT=`env TZ=Europe/London date`
	ET=`env TZ=America/New_York date`
	PT=`env TZ=US/Pacific date`
	HT=`env TZ=Pacific/Honolulu date`
	DT=`env TZ=Etc/GMT+12 date`
	#lang racket

	;;;; CPS translaions written with guidance from Ken Shan's notes
	;;;; and Danvy & Filinkski's paper Abstracting Control

	(define empty-env '())

	(define (extend-env name value env)
	(cons (list name value) env))
	#!/usr/bin/env python3

	import click
	import numpy as np
	import sys


	class IntOrStr(click.ParamType):
	name = 'int/str'
	{-# LANGUAGE FlexibleInstances #-}

	-- \| An implementation of Section 3, Local Type Argument Synthesis, from the
	-- paper /Local Type Inference/ by Pierce and Turner.
	module Infer where

	import Control.Monad (foldM, join, zipWithM)
	import Data.Function (on)
	import Data.List (foldl', groupBy, intercalate, intersect, nub)