Giseop Kim gisbi-kim

약자	한국정보과학회 (2024)	BK21플러스 IF (2018)	KAIST CS (2022)	SNU CSE (2024.4)	POSTECH CSE (2024.9)	평균 (정규화)	학회명	DBLP Key
AAAI	최우수	4	O	O	최우수	1.00	AAAI Conference on Artificial Intelligence (AAAI)	conf/aaai
AAMAS	우수	2				0.20	International Conference on Autonomous Agents and Multiagent Systems (AAMAS)	conf/ifaamas
ACCV	우수	1			우수	0.25	Asian Conference on Computer Vision (ACCV)	conf/accv
ACL	최우수	4	O	O	최우수	1.00	Annual Meeting of the Association for Computational Linguistics (ACL)	conf/acl
ACL Findings	우수				우수	0.20	Findings of ACL	series/findacl
ACNS	우수					0.10	International Conference on Applied Cryptography and Network Security (ACNS)	conf/acns
ACSAC	우수	2			우수	0.30	Annual Computer Security Applications Conference (ACSAC)	conf/acsac
AIED					우수	0.10	International Conference on Artificial Intelligence in Education (AIED)	conf/aied
AISTATS	우수	1			우수	0.25	International Conference on Artificial Intelligence and Statistics (AISTATS)	conf/aistats

CMake를 왜 쓰는거죠?
좋은 툴은 Visual Studio 뿐입니다. 그 이외에는 전부 사도(邪道)입니다 사도! - 작성자

주의

이 문서는 CMake를 주관적으로 서술합니다
이 문서를 통해 CMake를 시작하기엔 적합하지 않습니다
https://cgold.readthedocs.io/en/latest/ 3.1 챕터까지 따라해본 이후 기본사항들을 속성으로 익히는 것을 돕기위한 보조자료로써 작성되었습니다

Effective Modern CMake

Getting Started

For a brief user-level introduction to CMake, watch C++ Weekly, Episode 78, Intro to CMake by Jason Turner. LLVM’s CMake Primer provides a good high-level introduction to the CMake syntax. Go read it now.

After that, watch Mathieu Ropert’s CppCon 2017 talk Using Modern CMake Patterns to Enforce a Good Modular Design (slides). It provides a thorough explanation of what modern CMake is and why it is so much better than “old school” CMake. The modular design ideas in this talk are based on the book [Large-Scale C++ Software Design](https://www.amazon.de/Large-Scale-Soft

How to convert markdown to PDF:

This post reviews several methods for converting a Markdown (.md) formatted file to PDF, from UNIX or Linux machines.

Using `Pandoc`:

$ pandoc How_I_got_svg-resizer_working_on_Mac_OSX.md -s -o test1.pdf

	"""
	stable diffusion dreaming
	creates hypnotic moving videos by smoothly walking randomly through the sample space

	example way to run this script:

	$ python stablediffusionwalk.py --prompt "blueberry spaghetti" --name blueberry

	to stitch together the images, e.g.:
	$ ffmpeg -r 10 -f image2 -s 512x512 -i blueberry/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p blueberry.mp4

	%% Understanding how a constrastive loss works

	% constrastive loss refs:
	% - Kihyuk Sohn. Improved deep metric learning with multi- class n-pair loss objective. In Advances in Neural Informa- tion Processing Systems (NeurIPS), 2016.
	% - Aaron van den Oord, Yazhe Li, and Oriol Vinyals. Repre- sentation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748, 2018.
	% - Zaiwei Zhang et al. Self-Supervised Pretraining of 3D Features on any Point-Cloud, 2021

	%% param
	num_negs = 100;

	import torch
	from torch.utils.data import Dataset, DataLoader
	import numpy as np


	class MyDataset(Dataset):
	def __init__(self):
	x = np.random.rand(1000, 3) # 1000 3-dim samples
	self.x = [x[i].tolist() for i in range(1000)]
	y = np.random.randint(low=0, high=2, size=(1000,))

	# WARNING: These steps seem to not work anymore!

	#!/bin/bash

	# Purge existign CUDA first
	sudo apt --purge remove "cublas" "cuda"
	sudo apt --purge remove "nvidia*"

	# Install CUDA Toolkit 10
	wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb

	import numpy as np
	import scipy.linalg
	import scipy.stats
	import matplotlib.pyplot as plt
	import scipy.io
	import scipy.sparse
	from plot_helper import plot_cov_ellipse
	from tqdm import tqdm

	def R(theta):

	# This is an implementation of Occupancy Grid Mapping as Presented
	# in Chapter 9 of "Probabilistic Robotics" By Sebastian Thrun et al.
	# In particular, this is an implementation of Table 9.1 and 9.2


	import scipy.io
	import scipy.stats
	import numpy as np
	import matplotlib.pyplot as plt
	from tqdm import tqdm

Giseop Kim gisbi-kim

주의

Effective Modern CMake

Getting Started

How to convert markdown to PDF:

Using Pandoc:

Using `Pandoc`: