Awesome List Updates on Mar 17, 2021
14 awesome lists updated today.
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1. Awesome Django
Third-Party Packages / Commands
- django-liquidb (⭐27) - Django application to simplify migration management and changes in states of db scheme.
2. Awesome Arch
AUR Helpers / Pacman wrappers
- Paru (⭐7k) (Rust) - AUR helper with all needed modern wrapper features, created by a former developer of yay.
3. Awesome Javascript
Security / Runner
- sanitize-html (⭐4k) - sanitize-html provides a simple HTML sanitizer with a clear API.
4. Awesome React Native
Open Source Apps / Navigation Demos
- Artsy (⭐3.7k) - The mobile app for artsy.net. Discover fine Art. The Art world in your Pocket.
5. 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.
6. Awesome PICO 8
Contents / Community
Contents / DemoScene
7. Awesome Rails
Articles / Other external resources
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 (⭐247) - A community management app (using Rails 5.2).
- kanban (⭐644) - 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 (⭐139) - An inventory management app (using Rails 6.0). - 🌍
- sanataro (⭐52) - An account tracker (using Rails 4.2).
Gems / Other external resources
- actioncable (⭐57k) - A gem to integrate websocket with a Rails app 🔴 - Action Cable Overview
- actionmailbox (⭐57k) - A gem to handle incoming emails within a Rails app 🔴 - Action Mailbox Basics
- actionmailer (⭐57k) - A gem to compose, deliver & test emails within a Rails app 🔴 - Action Mailer Basics
- actionpack (⭐57k) - A gem to manage requests & responses within a Rails app 🔴
- actiontext (⭐57k) - A gem to integrate rich text editor into a Rails app 🔴 - Action Text Overview
- actionview (⭐57k) - A gem to handle view templates within a Rails app 🔴 - Action View Overview
- activejob (⭐57k) - A gem to handle background jobs within a Rails app 🔴 - Active Job Basics
- activemodel (⭐57k) - A gem to define a set of interfaces to use in model classes within a Rails app 🔴 - Active Model Basics
- activerecord (⭐57k) - A gem to connect model classes with relational databases within a Rails app 🔴 - Active Record Basics
- activestorage (⭐57k) - A gem to handle file uploads to cloud storage providers within a Rails app 🔴 - Active Storage Overview
- activesupport (⭐57k) - A gem to provide some extensions to support a Rails app 🔴 - Active Support Core Extensions
- railties (⭐57k) - A gem to handle gems & engines used in a Rails app to work together 🔴
8. Awesome Spark
Packages / Monitoring
- Data Mechanics Delight (⭐344)
- Cross-platform monitoring tool (Spark UI / Spark History Server replacement).
9. Awesome Free Software
Resources / Documentaries
10. Awesome Ios Books
🇷🇺 Russian books
11. Open Source Flutter Apps
Contents / News and Magazine
- InNews (⭐19) - Live News in eight different categories by Akash Lilhare.
12. Awesome Algorithms
Websites
- redblobgames - interactive visual explanations of math and algorithms, using motivating examples from computer games.
13. Awesome Electron
Closed Source / Other
- Discord - Voice and text chat.
14. Awesome Flutter
UI / Bottom bars
- Google Nav Bar (⭐765) - A modern google style nav bar for flutter by Sooxt98
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