Pinned Repositories
annotated_latex_equations
Examples of how to create colorful, annotated equations in Latex using Tikz.
causal_learning_unknown_interventions
Code for "Neural causal learning from unknown interventions"
CausalWorld
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
Computer_vision
This is a repository of google colabs related to computer vision
DanielF29.github.io
Deep-Taylor-Decomposition
DTD implement on Imagenet pretrained model
DoWhy
Exploration of Microsoft's Python package of the same name for observational studies
HyperBlog
Un Blog increible para el curso de Git y Github de Platzi
PlotNeuralNet
Latex code for making neural networks diagrams
Prototipical_Parts
Repository with some codes to train and test ProtoPNets (Thanks to the autors of ProtoPNet)
DanielF29's Repositories
DanielF29/Prototipical_Parts
Repository with some codes to train and test ProtoPNets (Thanks to the autors of ProtoPNet)
DanielF29/annotated_latex_equations
Examples of how to create colorful, annotated equations in Latex using Tikz.
DanielF29/HyperBlog
Un Blog increible para el curso de Git y Github de Platzi
DanielF29/PlotNeuralNet
Latex code for making neural networks diagrams
DanielF29/causal_learning_unknown_interventions
Code for "Neural causal learning from unknown interventions"
DanielF29/CausalWorld
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
DanielF29/Computer_vision
This is a repository of google colabs related to computer vision
DanielF29/DanielF29.github.io
DanielF29/Deep-Taylor-Decomposition
DTD implement on Imagenet pretrained model
DanielF29/DoWhy
Exploration of Microsoft's Python package of the same name for observational studies
DanielF29/dowhy-1
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
DanielF29/first-order-model
This repository contains the source code for the paper First Order Motion Model for Image Animation
DanielF29/google-research
Google Research
DanielF29/Grad-CAM_tests
DanielF29/hyperblog-1
Un blog increíble para el curso de Git y Github de Platzi
DanielF29/Netlogo_Complexity-measurement-on-a-MAS
6 similar codes of MAS on Netlogo testing a way for complexity measurement (based on Shannon Entropy) and comparisons between them
DanielF29/perceiver-pytorch
Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch
DanielF29/Plots
Repository to share code to generate different kinds of plots
DanielF29/PPs_ICNN_Loss
ProtoPNet with ICNN Loss
DanielF29/ProtoPNet
This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpretable Image Recognition" (to appear at NeurIPS 2019), by Chaofan Chen* (Duke University), Oscar Li* (Duke University), Chaofan Tao (Duke University), Alina Jade Barnett (Duke University), Jonathan Su (MIT Lincoln Laboratory), and Cynthia Rudin (Duke University) (* denotes equal contribution).
DanielF29/Python-Extension
Python extension for NetLogo
DanielF29/PythonExtension
Python extension for NetLogo
DanielF29/PyTorch-VAE
A Collection of Variational Autoencoders (VAE) in PyTorch.
DanielF29/SC2-Q-Learning
Codes on SCLE 2.0 with Zerg race using Q-learning
DanielF29/Simple-CartPole-NN-using-PyTorch-and-OpenAI-Gym
Simple CartPole controled by a NN using PyTorch and OpenAI Gym