Repositorio de los Laboratorios de Análisis Numérico / Análisis Numérico I de FAMAF, UNC.

Overview

Repositorio de los Laboratorios de Análisis Numérico / Análisis Numérico I de FAMAF, UNC.

Para los Laboratorios de la materia, vamos a utilizar el lenguaje de programación Python 3.X (donde X puede ser cualquier número mayor o igual a 5).

  • Tutorial para crear cuentas de UNC alumnos en este enlace.
  • Para instalar Python en sus computadoras, pueden seguir la página https://tutorial.djangogirls.org/es/python_installation/, tiene un buen tutorial para comenzar. En caso de querer una ayuda un poco más visual, recomendamos seguir este video.
  • Para poder crear el código que van a ejecutar, les recomendamos utilizar Visual Studio Code: https://code.visualstudio.com/. Este editor tiene la capacidad de agregar extensiones que facilitan un poco el trabajo con Python, pueden buscar la extensión llamada Python que aparece en la sección de Extensiones una vez que tengan instalado VSCode.
  • Para aquellas personas que solamente puedan usar el celular para realizar los laboratorios, es posible descargar la aplicación Google Colab Android View (Enlace a Google Play), que les permite utilizar y ejecutar código Python en celdas.

Playlists de Clases de Ediciones Anteriores

Owner
Luis Biedma
Mathematician and Data Scientist.
Luis Biedma
Single-step adversarial training (AT) has received wide attention as it proved to be both efficient and robust.

Subspace Adversarial Training Single-step adversarial training (AT) has received wide attention as it proved to be both efficient and robust. However,

15 Sep 02, 2022
A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network"

DGC-Net: Dense Geometric Correspondence Network This is a PyTorch implementation of our work "DGC-Net: Dense Geometric Correspondence Network" TL;DR A

191 Dec 16, 2022
[ICCV 2021] FaPN: Feature-aligned Pyramid Network for Dense Image Prediction

FaPN: Feature-aligned Pyramid Network for Dense Image Prediction [arXiv] [Project Page] @inproceedings{ huang2021fapn, title={{FaPN}: Feature-alig

EMI-Group 175 Dec 30, 2022
A hue shift helper for OBS

obs-hue-shift A hue shift helper for OBS This is a repo based on the really nice script Hegemege made. The original script can be found https://gist.g

Alexis Tyler 1 Jan 10, 2022
An implementation of the AdaOPS (Adaptive Online Packing-based Search), which is an online POMDP Solver used to solve problems defined with the POMDPs.jl generative interface.

AdaOPS An implementation of the AdaOPS (Adaptive Online Packing-guided Search), which is an online POMDP Solver used to solve problems defined with th

9 Oct 05, 2022
Pytorch implementation of Implicit Behavior Cloning.

Implicit Behavior Cloning - PyTorch (wip) Pytorch implementation of Implicit Behavior Cloning. Install conda create -n ibc python=3.8 pip install -r r

Kevin Zakka 49 Dec 25, 2022
ConvMixer unofficial implementation

ConvMixer ConvMixer 非官方实现 pytorch 版本已经实现。 nets 是重构版本 ,test 是官方代码 感兴趣小伙伴可以对照看一下。 keras 已经实现 tf2.x 中 是tensorflow 2 版本 gelu 激活函数要求 tf=2.4 否则使用入下代码代替gelu

Jian Tengfei 8 Jul 11, 2022
Pytorch implementation of our paper LIMUSE: LIGHTWEIGHT MULTI-MODAL SPEAKER EXTRACTION.

LiMuSE Overview Pytorch implementation of our paper LIMUSE: LIGHTWEIGHT MULTI-MODAL SPEAKER EXTRACTION. LiMuSE explores group communication on a multi

Auditory Model and Cognitive Computing Lab 17 Oct 26, 2022
Code for ICML 2021 paper: How could Neural Networks understand Programs?

OSCAR This repository contains the source code of our ICML 2021 paper How could Neural Networks understand Programs?. Environment Run following comman

Dinglan Peng 115 Dec 17, 2022
Reinforcement learning models in ViZDoom environment

DoomNet DoomNet is a ViZDoom agent trained by reinforcement learning. The agent is a neural network that outputs a probability of actions given only p

Andrey Kolishchak 126 Dec 09, 2022
PyTorch reimplementation of REALM and ORQA

PyTorch reimplementation of REALM and ORQA

Li-Huai (Allan) Lin 17 Aug 20, 2022
Self-supervised learning (SSL) is a method of machine learning

Self-supervised learning (SSL) is a method of machine learning. It learns from unlabeled sample data. It can be regarded as an intermediate form between supervised and unsupervised learning.

Ashish Patel 4 May 26, 2022
YOLO5Face: Why Reinventing a Face Detector (https://arxiv.org/abs/2105.12931)

Introduction Yolov5-face is a real-time,high accuracy face detection. Performance Single Scale Inference on VGA resolution(max side is equal to 640 an

DeepCam Shenzhen 1.4k Jan 07, 2023
Pytorch implementation for the EMNLP 2020 (Findings) paper: Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering

Path-Generator-QA This is a Pytorch implementation for the EMNLP 2020 (Findings) paper: Connecting the Dots: A Knowledgeable Path Generator for Common

Peifeng Wang 33 Dec 05, 2022
Joint Gaussian Graphical Model Estimation: A Survey

Joint Gaussian Graphical Model Estimation: A Survey Test Models Fused graphical lasso [1] Group graphical lasso [1] Graphical lasso [1] Doubly joint s

Koyejo Lab 1 Aug 10, 2022
SAT: 2D Semantics Assisted Training for 3D Visual Grounding, ICCV 2021 (Oral)

SAT: 2D Semantics Assisted Training for 3D Visual Grounding SAT: 2D Semantics Assisted Training for 3D Visual Grounding by Zhengyuan Yang, Songyang Zh

Zhengyuan Yang 22 Nov 30, 2022
Code for the paper "Improved Techniques for Training GANs"

Status: Archive (code is provided as-is, no updates expected) improved-gan code for the paper "Improved Techniques for Training GANs" MNIST, SVHN, CIF

OpenAI 2.2k Jan 01, 2023
Deep Surface Reconstruction from Point Clouds with Visibility Information

Data, code and pretrained models for the paper Deep Surface Reconstruction from Point Clouds with Visibility Information.

Raphael Sulzer 23 Jan 04, 2023
SciFive: a text-text transformer model for biomedical literature

SciFive SciFive provided a Text-Text framework for biomedical language and natural language in NLP. Under the T5's framework and desrbibed in the pape

Long Phan 54 Dec 24, 2022
An unofficial personal implementation of UM-Adapt, specifically to tackle joint estimation of panoptic segmentation and depth prediction for autonomous driving datasets.

Semisupervised Multitask Learning This repository is an unofficial and slightly modified implementation of UM-Adapt[1] using PyTorch. This code primar

Abhinav Atrishi 11 Nov 25, 2022