jarmitage

@incollection{andersonImagerySpatialRepresentation2017,
  title = {Imagery and {{Spatial Representation}}},
  booktitle = {A {{Companion}} to {{Cognitive Science}}},
  author = {Anderson, Rita E.},
  year = {2017},
  pages = {204--211},
  publisher = {{John Wiley \& Sons, Ltd}},
  doi = {10.1002/9781405164535.ch12},
  abstract = {Take a moment to use mental imagery to perform the following tasks: (1) decide whether an apple is more similar in shape to a banana or an orange, (2) determine how to rearrange the furniture in your bedroom to make room for a new dresser, and (3) drive home during rush hour. Although we take our ability to perform tasks such as these for granted, they raise a host of interesting questions about imagery. For instance, what is the relationship between imagery and perception? What types of processes are needed to account for our ability to generate, maintain, transform, and inspect images? How do we characterize individual differences in imagery ability? What is the relation between im

jarmitage

\begin{abstract}
% General idea / area / issue

% More specific

% What we did

% Specifically what we did

% What happened

jarmitage

let utter = u => speechSynthesis.speak(new SpeechSynthesisUtterance(u))

jarmitage

do -- 'do blocks' run all the code below at the same time
  setcps (120/60/4) -- 120 cycles per second with 4 beats per bar
  let mx = [0,0,0,0] -- mixer (gain control) for each pattern
  d1 $ stack [
    s "bd*4",
    s "[~ sn]*2",
    s "[~ hc]*4"
  ] # gain (mx!!0) -- 1st item in mx list
  d2
    $ struct "t(3,8) t(5,8" -- structure

jarmitage

SOFIE

Code generation for fast inference of Deep Learning models ROOT/TMVA SOFIE (“System for Optimized Fast Inference code Emit”) is a new package introduced in this release that generates C++ functions easily invokable for the fast inference of trained neural network models. It takes ONNX model files as inputs and produces C++ header files that can be included and utilized in a “plug-and-go” style. This is a new development and it is currently still in experimental stage. SOFIE can take your trained ONNX model and generate blazingly fast C++ code from it, depending only on BLAS.

• Announcement https://root.cern/doc/v626/release-notes.html#sofie-code-generation-for-fast-inference-of-deep-learning-models
• SOFIE was created by Sitong An https://sitongan.github.io/ a Marie Curie Fellow at CERN
• Supported ONNX operators: https://github.com/root-project/root/blob/master/tmva/sofie/inc/TMVA/OperatorList.hxx
• SOFIE is part of TMVA, the ROOT Machine Learning library https://root.cern/manual/tmva/

jarmitage

<script>
    import { onMount } from 'svelte'
    import { SomethingStore as Something } from '../../stores/somethingStore'
    import Component from './Component.svelte'
  
    $: stuff = $Something.stuff

    let didMount = false

    onMount(async () => {

jarmitage

# super rough code!
# only supports simple tex + ssml
# requires sox for audio concatenation

# %autoawait - if in .ipynb, this is needed for async to work

import pypandoc
import html
import re
import os

jarmitage

@article{aktasYouHaveOne2021,
  title = {You {{Have One New Message}}: {{Knitting}} Intimacy for Connecting Opinions, People and the World},
  shorttitle = {You {{Have One New Message}}},
  author = {Aktas, Bilge Merve},
  year = {2021},
  month = may,
  volume = {14},
  issn = {1890-9515},
  doi = {10.7577/formakademisk.4174},

jarmitage

p1 $ slow (277/4)
  $ stack [
    n "d4 ~ ~ ~ ~ ~ ~ ~ d5 ~ ~ ~ a4 ~ ~ ~ ~ ~ ~ ~ g5 ~ ~ ~ d4 ~ ~ ~ ~ ~ ~ ~ fs5 ~ ~ ~ a4 ~ ~ ~ ~ ~ ~ ~ b5 ~ ~ ~ a5 ~ ~ ~ b5 ~ ~ ~ a5 ~ ~ ~ g5 ~ ~ ~ e5 ~ ~ ~ b5 ~ ~ ~ d6 ~ ~ ~ d5 ~ ~ ~ fs5 ~ ~ ~ b5 ~ ~ ~ ~ ~ cs6 ~ d6 ~ e6 ~ fs6 ~ ~ ~ g6 ~ ~ ~ fs6 ~ ~ ~ g5 ~ ~ ~ e5 ~ ~ ~ b5 ~ ~ ~ cs6 ~ ~ ~ d5 ~ ~ ~ fs5 ~ ~ ~ b5 ~ ~ ~ ~ ~ ~ ~ e6 ~ ~ ~ fs6 ~ ~ ~ g6 ~ ~ ~ fs6 ~ ~ ~ e6 ~ ~ ~ g4 ~ ~ ~ ~ ~ ~ ~ d6 ~ ~ ~ fs6 ~ ~ ~ e6 ~ ~ ~ d6 ~ ~ ~ g5 ~ ~ ~ b5 ~ ~ ~ a5 ~ ~ ~ d5 ~ ~ ~ ~ ~ ~ ~ a3 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ d3 ~ ~ ~ ~ ~ ~ ~ d5 ~ ~ ~ a3 ~ ~ ~ ~ ~ ~ ~ g5 ~ ~ ~ d4 ~ ~ ~ ~ ~ ~ ~ a5 ~ ~ ~ a4 ~ ~ ~ ~ ~ ~ ~ b5 ~ ~ ~ a5 ~ ~ ~ b5 ~ ~ ~ a5 ~ ~ ~ g5 ~ ~ ~ e5 ~ ~ ~ b5 ~ ~ ~ d6 ~ ~ ~ d5 ~ ~ ~ fs5 ~ ~ ~ b5 ~ ~ ~ ~ ~ cs6 ~ d6 ~ e6 ~ fs6 ~ ~ ~ g6 ~ ~ ~ fs6 ~ ~ ~ e6 ~ ~ ~ g5 ~ ~ ~ b5 ~ ~ ~ cs6 ~ ~ ~ d5 ~ ~ ~ fs5 ~ ~ ~ b5 ~ ~ ~ ~ ~ ~ ~ e6 ~ ~ ~ fs6 ~ ~ ~ g6 ~ ~ ~ fs6 ~ ~ ~ e6 ~ ~ ~ g4 ~ ~ ~ ~ ~ ~ ~ d6 ~ ~ ~ fs6 ~ ~ ~ e6 ~ ~ ~ d6 ~ ~ ~ g5 ~ ~ ~ b5 ~ ~ ~ a5 ~ ~ ~ d5 ~ ~ ~ d5 ~ ~ ~ cs5 ~ ~ ~ a4 ~ ~ ~ ~ ~ ~ ~ fs5 ~ ~ ~

jarmitage

%%
%% This is file `progress.sty',
%%
%% version 1.10
%%
%% Copyright (C) 2002-2003 Kasper B. Graversen - this is freeware
%%
%% Thanks to Robin Fairbairns for helping me sorting things out ;-)
%% Thanks to Dan Luecking for some definitions
%% Also thanks to David Bausum for his free 'trept' "TeX: Reference and Examples" information material