#
explanations
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RobertSamoilescu
commented
Jun 14, 2021
Consider adding explicit type hints in TabularSampler for feature_names: list, feature_values: dict and others.
moDel Agnostic Language for Exploration and eXplanation
black-box
data-science
machine-learning
predictive-modeling
fairness
interpretability
explainable-artificial-intelligence
explanations
explainable-ai
explainable-ml
xai
model-visualization
interpretable-machine-learning
iml
dalex
responsible-ai
responsible-ml
explanatory-model-analysis
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Aug 24, 2021 - Python
Everything you need to know about Shadow DOM
css
examples
guide
web-components
custom-elements
questions
slot
shadow-dom
document-fragment
explanations
doubts
shadow-roots
light-dom-elements
shadow-trees
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May 18, 2021
A collection of common algorithms and data structures implemented in java, c++, and python.
java
ai
neural-network
algorithms
cpp
graph-algorithms
trie
python3
bit-manipulation
data-structures
neural-networks
sorting-algorithms
dynamic-programming
trees
tested
interview-preparation
explanations
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Apr 25, 2021 - Java
Repository for the Explainable Deep One-Class Classification paper
python
machine-learning
deep-learning
pytorch
anomaly-detection
one-class-learning
explanations
xai
deep-anomaly-detection
explainable-deepneuralnetwork
mvtec-ad
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Jul 12, 2021 - Python
InterpretDL: Interpretation of Deep Learning Models，基于『飞桨』的模型可解释性算法库
grad-cam
convolutional-neural-networks
visualizations
lime
paddlepaddle
model-interpretation
nlp-models
smoothgrad
explanations
vision-transformer
interpretation-algorithms
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Jul 22, 2021 - Jupyter Notebook
Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
machine-learning
paper
lime
interpretability
adversarial-attacks
explanations
shap
post-hoc-explanation
fool-lime
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Jun 8, 2021 - Jupyter Notebook
A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).
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Feb 19, 2021 - Python
Explaining dimensionality results using SHAP values
machine-learning
dimensionality-reduction
visualizations
explanations
explainable-ai
explainable-ml
cluster-formation
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May 30, 2021 - Jupyter Notebook
Awesome Explainable AI (XAI) and Interpretable ML Papers and Resources
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May 4, 2021
General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems
library
reinforcement-learning
rl
model-extraction
lime
plug-and-play
interpretability
reinforcement-learning-agent
open-ai
abstract-argumentation
explanations
xai
multi-agent-reinforcement-learning
open-ai-gym
knowledge-extraction
explainability
marl
model-extractor
extracting-interpretable-models
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May 10, 2020 - C++
PowerShell version of explainshell.com
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Aug 20, 2021 - C#
Robust Attribution Regularization
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Oct 7, 2020 - Jupyter Notebook
The unofficial devRant API documentation
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Nov 18, 2020 - API Blueprint
Anupam Datta, Matt Fredrikson, Klas Leino, Kaiji Lu, Shayak Sen, Zifan Wang
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Feb 23, 2021
Many time, when an interview approaches, candidates start searching for different algorithms in different programming languages for practise. This project aims to build a website which will contain the codes along with the techniques and explanations so that it can be helpful for many
bootstrap
html5
algorithms
datastructures
cpp
css3
bootstrap4
python3
programming-languages
practise
explanations
interview-approaches
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Oct 1, 2020 - JavaScript
A self learning exercise in low level system programming (OS and kernel programming) for the x86 architecture.
kernel
hardware
architecture
osdev
operating-system
qemu
learning-exercise
drivers
learning-by-doing
kernel-source
operating-system-learning
explanations
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Jun 23, 2021 - C
Triplot: Instance- and data-level explanations for the groups of correlated features.
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Mar 10, 2021 - R
[Python] Code repository for "A Deep Adversarial Framework for Visually Explainable Periocular Recognition", as seen in CVPR 2021 Biometrics Workshop
deep-learning
pytorch
biometrics
interpretability
cvprw
explanations
periocular-recognition
periocular-biometrics
deep-adversarial-framework
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Aug 23, 2021 - Python
Master thesis work: explaining deep reinforcement learning policies
machine-learning
reinforcement-learning
deep-learning
explanation
hierarchical-reinforcement-learning
explanations
explainable-ai
high-level-plan
hierarchical-agents
subgoals
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Aug 27, 2020 - Jupyter Notebook
A list of research papers of explainable machine learning.
machine-learning
awesome
research
paper
academic
survey
human-in-the-loop
interpretability
human-in-the-loop-machine-learning
explanations
interpretable-ml
explainable-ml
xai
explainability
counterfactual-explanations
interpretable-models
recourse
trustworthy-machine-learning
human-ai-interaction
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Jun 25, 2021
Implementation of ExCut: Explainable Embedding-based Clustering over Knowledge Graphs
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Jul 7, 2021 - Python
Terms, Abbreviations, Mnemonics, etc used in Software Development/Engineering.
web-development
solid
oop
principles
software-engineering
software-development
behavior-driven-development
abbreviations
test-driven-development
oop-principles
terminologies
web-developer
acidbase
mnemonics
tight-coupling
explanations
yagni
loose-coupling
cap-theorem
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Jul 17, 2020
A human-centric explainable approach for fake news spreading detection on Twitter threads
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Jun 11, 2021 - Python
A collection of intuitive explanations and short summaries (hence the name "Intuitive Shorts") of important and interesting ML/NLP/CV concepts
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May 17, 2021
This is my tutorial to help those that want to learn how to code that have no prior experience.
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Jan 3, 2021 - Python
A provenance tree generator for recursive Datalog with negation (and Dedalus).
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Jun 23, 2018 - Python
A PyTorch based implementation of MMD-critic
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Nov 12, 2020 - Python
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What is there in
Coin Change.md?Only a variation of unbounded Knapsack
Issue:
There exists many more variations like having a fixed number of coins or say a problem where we want to find the number of ways (ordered) a sum of money can be formed
Suggested Solution:
We can add these two explanations separately in files.