Awesome List Updates on Mar 17, 2021

18 awesome lists updated today.

🏠 Home · 🔍 Search · 🔥 Feed · 📮 Subscribe · ❤️ Sponsor

1. Awesome Django

Third-Party Packages / Commands

django-liquidb (⭐18) - Django application to simplify migration management and changes in states of db scheme.

2. Awesome Arch

AUR Helpers / Pacman wrappers

Paru (⭐4.4k) (Rust) - AUR helper with all needed modern wrapper features, created by a former developer of yay.

3. Awesome Javascript

Security / Runner

sanitize-html (⭐3.5k) - sanitize-html provides a simple HTML sanitizer with a clear API.

4. Awesome React Native

Open Source Apps / Navigation Demos

Artsy (⭐3.1k) - The mobile app for artsy.net. Discover fine Art. The Art world in your Pocket.

5. Awesome Nextjs

Boilerplates

superplate (⭐2.7k) - superplate creates Next.js app in seconds with TypeScript, styled-components, SWR, Storybook, and 35+ plugin.

6. Awesome Xai

Papers / Landmarks

Explanation in Artificial Intelligence: Insights from the Social Sciences - This paper provides an introduction to the social science research into explanations. The author provides 4 major findings: (1) explanations are constrastive, (2) explanations are selected, (3) probabilities probably don't matter, (4) explanations are social. These fit into the general theme that explanations are -contextual-.

Sanity Checks for Saliency Maps - An important read for anyone using saliency maps. This paper proposes two experiments to determine whether saliency maps are useful: (1) model parameter randomization test compares maps from trained and untrained models, (2) data randomization test compares maps from models trained on the original dataset and models trained on the same dataset with randomized labels. They find that "some widely deployed saliency methods are independent of both the data the model was trained on, and the model parameters".

Papers / Surveys

Explainable Deep Learning: A Field Guide for the Uninitiated - An in-depth description of XAI focused on technqiues for deep learning.

Papers / Evaluations

Quantifying Explainability of Saliency Methods in Deep Neural Networks - An analysis of how different heatmap-based saliency methods perform based on experimentation with a generated dataset.

Papers / XAI Methods

Ada-SISE - Adaptive semantice inpute sampling for explanation.

ALE - Accumulated local effects plot.

ALIME - Autoencoder Based Approach for Local Interpretability.

Anchors - High-Precision Model-Agnostic Explanations.

Auditing - Auditing black-box models.

BayLIME - Bayesian local interpretable model-agnostic explanations.

Break Down - Break down plots for additive attributions.

CAM - Class activation mapping.

CDT - Confident interpretation of Bayesian decision tree ensembles.

CICE - Centered ICE plot.

CMM - Combined multiple models metalearner.

Conj Rules - Using sampling and queries to extract rules from trained neural networks.

CP - Contribution propogation.

DecText - Extracting decision trees from trained neural networks.

DeepLIFT - Deep label-specific feature learning for image annotation.

DTD - Deep Taylor decomposition.

ExplainD - Explanations of evidence in additive classifiers.

FIRM - Feature importance ranking measure.

Fong, et. al. - Meaninful perturbations model.

G-REX - Rule extraction using genetic algorithms.

Gibbons, et. al. - Explain random forest using decision tree.

GoldenEye - Exploring classifiers by randomization.

GPD - Gaussian process decisions.

GPDT - Genetic program to evolve decision trees.

GradCAM - Gradient-weighted Class Activation Mapping.

GradCAM++ - Generalized gradient-based visual explanations.

Hara, et. al. - Making tree ensembles interpretable.

ICE - Individual conditional expectation plots.

IG - Integrated gradients.

inTrees - Interpreting tree ensembles with inTrees.

IOFP - Iterative orthoganol feature projection.

IP - Information plane visualization.

KL-LIME - Kullback-Leibler Projections based LIME.

Krishnan, et. al. - Extracting decision trees from trained neural networks.

Lei, et. al. - Rationalizing neural predictions with generator and encoder.

LIME - Local Interpretable Model-Agnostic Explanations.

LOCO - Leave-one covariate out.

LORE - Local rule-based explanations.

Lou, et. al. - Accurate intelligibile models with pairwise interactions.

LRP - Layer-wise relevance propogation.

MCR - Model class reliance.

MES - Model explanation system.

MFI - Feature importance measure for non-linear algorithms.

NID - Neural interpretation diagram.

OptiLIME - Optimized LIME.

PALM - Partition aware local model.

PDA - Prediction Difference Analysis: Visualize deep neural network decisions.

PDP - Partial dependence plots.

POIMs - Positional oligomer importance matrices for understanding SVM signal detectors.

ProfWeight - Transfer information from deep network to simpler model.

Prospector - Interactive partial dependence diagnostics.

QII - Quantitative input influence.

REFNE - Extracting symbolic rules from trained neural network ensembles.

RETAIN - Reverse time attention model.

RISE - Randomized input sampling for explanation.

RxREN - Reverse engineering neural networks for rule extraction.

SHAP - A unified approach to interpretting model predictions.

SIDU - Similarity, difference, and uniqueness input perturbation.

Simonynan, et. al - Visualizing CNN classes.

Singh, et. al - Programs as black-box explanations.

STA - Interpreting models via Single Tree Approximation.

Strumbelj, et. al. - Explanation of individual classifications using game theory.

SVM+P - Rule extraction from support vector machines.

TCAV - Testing with concept activation vectors.

Tolomei, et. al. - Interpretable predictions of tree-ensembles via actionable feature tweaking.

Tree Metrics - Making sense of a forest of trees.

TreeSHAP - Consistent feature attribute for tree ensembles.

TreeView - Feature-space partitioning.

TREPAN - Extracting tree-structured representations of trained networks.

TSP - Tree space prototypes.

VBP - Visual back-propagation.

VEC - Variable effect characteristic curve.

VIN - Variable interaction network.

X-TREPAN - Adapted etraction of comprehensible decision tree in ANNs.

Xu, et. al. - Show, attend, tell attention model.

Papers / Critiques

Attention is not Explanation - Authors perform a series of NLP experiments which argue attention does not provide meaningful explanations. They also demosntrate that different attentions can generate similar model outputs.

Attention is not --not-- Explanation - This is a rebutal to the above paper. Authors argue that multiple explanations can be valid and that the and that attention can produce a valid explanation, if not -the- valid explanation.

Do Not Trust Additive Explanations - Authors argue that addditive explanations (e.g. LIME, SHAP, Break Down) fail to take feature ineractions into account and are thus unreliable.

Please Stop Permuting Features An Explanation and Alternatives - Authors demonstrate why permuting features is misleading, especially where there is strong feature dependence. They offer several previously described alternatives.

Stop Explaining Black Box Machine Learning Models for High States Decisions and Use Interpretable Models Instead - Authors present a number of issues with explainable ML and challenges to interpretable ML: (1) constructing optimal logical models, (2) constructing optimal sparse scoring systems, (3) defining interpretability and creating methods for specific methods. They also offer an argument for why interpretable models might exist in many different domains.

The (Un)reliability of Saliency Methods - Authors demonstrate how saliency methods vary attribution when adding a constant shift to the input data. They argue that methods should fulfill input invariance, that a saliency method mirror the sensistivity of the model with respect to transformations of the input.

Follow / Critiques

The Institute for Ethical AI & Machine Learning - A UK-based research center that performs research into ethical AI/ML, which frequently involves XAI.

Tim Miller - One of the preeminent researchers in XAI.

7. Awesome PICO 8

Contents / Community

Pico-8 Wiki

Contents / DemoScene

Pico-8 demos on Pouet

8. Awesome Rails

Articles / Other external resources

More than "Hello World" in Docker: Build Rails + Sidekiq web apps in Docker

How To Add Stimulus to a Ruby on Rails Application

Build a RESTful JSON API With Rails 5

Famous Web Apps Built with Ruby on Rails

Building a JSON API with Rails 5

Choosing ruby on rails for your next web development project (business guide)

How I used Docker with Rails

Open Source Rails Apps / Other external resources

asakusaSatellite (⭐101) - A realtime chat application for developers (using Rails 6.0). - 🌍

catarse (⭐1.6k) - A crowdfunding platform for creative projects (using Rails 4.2). - 🌍

commudle (⭐248) - A community management app (using Rails 5.2).

kanban (⭐642) - A Trello clone (using Rails 4.2).

opensourcefriday (⭐1.2k) - A project contribution tracking app (using Rails 6.0). - 🌍

peatio (⭐3.6k) - A crypto currency exchange app (using Rails 4.0).

reservations (⭐141) - An inventory management app (using Rails 6.0). - 🌍

rletters - A frontend for database of journal articles for researchers (using Rails 6.0).

sanataro (⭐52) - An account tracker (using Rails 4.2).

Gems / Other external resources

actioncable (⭐55k) - A gem to integrate websocket with a Rails app 🔴 - Action Cable Overview

actionmailbox (⭐55k) - A gem to handle incoming emails within a Rails app 🔴 - Action Mailbox Basics

actionmailer (⭐55k) - A gem to compose, deliver & test emails within a Rails app 🔴 - Action Mailer Basics

actionpack (⭐55k) - A gem to manage requests & responses within a Rails app 🔴

actiontext (⭐55k) - A gem to integrate rich text editor into a Rails app 🔴 - Action Text Overview

actionview (⭐55k) - A gem to handle view templates within a Rails app 🔴 - Action View Overview

activejob (⭐55k) - A gem to handle background jobs within a Rails app 🔴 - Active Job Basics

activemodel (⭐55k) - A gem to define a set of interfaces to use in model classes within a Rails app 🔴 - Active Model Basics

activerecord (⭐55k) - A gem to connect model classes with relational databases within a Rails app 🔴 - Active Record Basics

activestorage (⭐55k) - A gem to handle file uploads to cloud storage providers within a Rails app 🔴 - Active Storage Overview

activesupport (⭐55k) - A gem to provide some extensions to support a Rails app 🔴 - Active Support Core Extensions

railties (⭐55k) - A gem to handle gems & engines used in a Rails app to work together 🔴

9. Awesome Spark

Packages / Monitoring

Data Mechanics Delight (⭐303) - Cross-platform monitoring tool (Spark UI / Spark History Server replacement).

10. Awesome Playwright

Integrations

axe-playwright (⭐160) - Inofficial integration of Axe with Playwright.

11. Awesome Free Software

Resources / Documentaries

2019: Hacking for the Commons, by Philippe Borrel.

12. Awesome Tailwindcss

UI Libraries, Components & Templates

🧩 Tailwind Cards (⭐555) - Growing collection of text/image cards.

13. Vertx Awesome

Database Clients

Relational Databases
- Reactive SQL Client (⭐855) - High performance reactive SQL client.
- JDBC (⭐125) - Asynchronous interface around a JDBC datasource.
- MySQL / PostgreSQL (⭐115) - Asynchronous Client for MySQL/PostgreSQL.
- PostgreSQL (⭐72) - Reactive PostgreSQL Client.
- database (⭐39) - Client for Oracle, PostgreSQL, SQL Server, HyperSQL, etc. designed for security, correctness, and ease of use.
- jOOQ (⭐377) - Doing typesafe, asynchronous SQL and generate code using jOOQ.
- jOOQx (⭐20) - Leverages the power of typesafe SQL from jOOQ DSL and uses the reactive and non-blocking SQL driver from Vert.x.