All Projects → awesome-agi-cocosci → Similar Projects or Alternatives

167 Open source projects that are alternatives of or similar to awesome-agi-cocosci

symbolic-pymc
Tools for the symbolic manipulation of PyMC models, Theano, and TensorFlow graphs.
Stars: ✭ 58 (-28.4%)
Mutual labels:  bayesian
DataScience ArtificialIntelligence Utils
Examples of Data Science projects and Artificial Intelligence use cases
Stars: ✭ 302 (+272.84%)
Mutual labels:  explainable-ai
mllp
The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".
Stars: ✭ 15 (-81.48%)
Mutual labels:  explainable-ai
statistical-rethinking-solutions
Solutions of practice problems from the Richard McElreath's "Statistical Rethinking" book.
Stars: ✭ 60 (-25.93%)
Mutual labels:  bayesian
neuro-symbolic-sudoku-solver
⚙️ Solving sudoku using Deep Reinforcement learning in combination with powerful symbolic representations.
Stars: ✭ 60 (-25.93%)
Mutual labels:  explainable-ai
transformers-interpret
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
Stars: ✭ 861 (+962.96%)
Mutual labels:  explainable-ai
uk planning scraper
A Ruby gem to get planning applications data from UK council websites.
Stars: ✭ 19 (-76.54%)
Mutual labels:  planning
interval
This PHP library provides some tools to handle intervals. For instance, you can compute the union or intersection of two intervals.
Stars: ✭ 25 (-69.14%)
Mutual labels:  planning
probai-2019
Materials of the Nordic Probabilistic AI School 2019.
Stars: ✭ 127 (+56.79%)
Mutual labels:  bayesian
hierarchical-dnn-interpretations
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
Stars: ✭ 110 (+35.8%)
Mutual labels:  explainable-ai
PDDL.jl
Julia parser, interpreter and compiler interface for the Planning Domain Definition Language (PDDL). Planners not included.
Stars: ✭ 52 (-35.8%)
Mutual labels:  planning
fun-with-dnc
Pytorch Implementation of Deepmind's 'Hybrid computing using a neural network with dynamic external memory' (Differentiable Neural Computer) + some applications
Stars: ✭ 18 (-77.78%)
Mutual labels:  planning
fast-tsetlin-machine-with-mnist-demo
A fast Tsetlin Machine implementation employing bit-wise operators, with MNIST demo.
Stars: ✭ 58 (-28.4%)
Mutual labels:  explainable-ai
geostan
Bayesian spatial analysis
Stars: ✭ 40 (-50.62%)
Mutual labels:  bayesian
pymc3-hmm
Hidden Markov models in PyMC3
Stars: ✭ 81 (+0%)
Mutual labels:  bayesian
binary.com-interview-question
The sample question for Interview a job in Binary options
Stars: ✭ 52 (-35.8%)
Mutual labels:  bayesian
scrumonline
Always up to date scrumonline docker build
Stars: ✭ 18 (-77.78%)
Mutual labels:  planning
statrethink course in pymc3
Statistical Rethinking course in pymc3
Stars: ✭ 141 (+74.07%)
Mutual labels:  bayesian
tukey
Mini stats toolkit for Clojure/Script
Stars: ✭ 17 (-79.01%)
Mutual labels:  bayesian
PlanningSup
Planning universitaire réalisé en Nuxt.js
Stars: ✭ 16 (-80.25%)
Mutual labels:  planning
DiscEval
Discourse Based Evaluation of Language Understanding
Stars: ✭ 18 (-77.78%)
Mutual labels:  pragmatics
grasp
Essential NLP & ML, short & fast pure Python code
Stars: ✭ 58 (-28.4%)
Mutual labels:  explainable-ai
Relational Deep Reinforcement Learning
No description or website provided.
Stars: ✭ 44 (-45.68%)
Mutual labels:  explainable-ai
sr plan
Save and restore query plans in PostgreSQL
Stars: ✭ 57 (-29.63%)
Mutual labels:  planning
flyxc
GPS track visualization, flight planning, live tracking, and more ...
Stars: ✭ 47 (-41.98%)
Mutual labels:  planning
dlime experiments
In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).
Stars: ✭ 21 (-74.07%)
Mutual labels:  explainable-ai
autonomous-delivery-robot
Repository for Autonomous Delivery Robot project of IvLabs, VNIT
Stars: ✭ 65 (-19.75%)
Mutual labels:  planning
MTfit
MTfit code for Bayesian Moment Tensor Fitting
Stars: ✭ 61 (-24.69%)
Mutual labels:  bayesian
Transformer-MM-Explainability
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
Stars: ✭ 484 (+497.53%)
Mutual labels:  explainable-ai
Angry-HEX
An artificial player for the popular video game Angry Birds
Stars: ✭ 16 (-80.25%)
Mutual labels:  planning
copycat
Modern port of Melanie Mitchell's and Douglas Hofstadter's Copycat
Stars: ✭ 84 (+3.7%)
Mutual labels:  analogy
BotSmartScheduler
Enhance your planning capabilities with this smart bot!
Stars: ✭ 44 (-45.68%)
Mutual labels:  planning
concept-based-xai
Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
Stars: ✭ 41 (-49.38%)
Mutual labels:  explainable-ai
planner
Lightweight, interactive planning tool that visualizes a series of tasks using an HTML canvas
Stars: ✭ 502 (+519.75%)
Mutual labels:  planning
awesome-probabilistic-planning
A curated list of online resources for probabilistic planning: papers, software and research groups around the world!
Stars: ✭ 45 (-44.44%)
Mutual labels:  planning
walker
Bayesian Generalized Linear Models with Time-Varying Coefficients
Stars: ✭ 38 (-53.09%)
Mutual labels:  bayesian
panther
Perception-Aware Trajectory Planner in Dynamic Environments
Stars: ✭ 115 (+41.98%)
Mutual labels:  planning
BayesianSocialScience
사회과학자를 위한 데이터과학 방법론 (코드 저장소)
Stars: ✭ 22 (-72.84%)
Mutual labels:  bayesian
ordered
Entropy-controlled contexts in Python
Stars: ✭ 36 (-55.56%)
Mutual labels:  planning
go-topics
Latent Dirichlet Allocation
Stars: ✭ 23 (-71.6%)
Mutual labels:  bayesian
bert attn viz
Visualize BERT's self-attention layers on text classification tasks
Stars: ✭ 41 (-49.38%)
Mutual labels:  explainable-ai
javaAnchorExplainer
Explains machine learning models fast using the Anchor algorithm originally proposed by marcotcr in 2018
Stars: ✭ 17 (-79.01%)
Mutual labels:  explainable-ai
Dropout BBalpha
Implementations of the ICML 2017 paper (with Yarin Gal)
Stars: ✭ 40 (-50.62%)
Mutual labels:  bayesian
leap
Official codebase for LEAP: Planning with Goal Conditioned Policies
Stars: ✭ 38 (-53.09%)
Mutual labels:  planning
expmrc
ExpMRC: Explainability Evaluation for Machine Reading Comprehension
Stars: ✭ 58 (-28.4%)
Mutual labels:  explainable-ai
deep-explanation-penalization
Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584
Stars: ✭ 110 (+35.8%)
Mutual labels:  explainable-ai
3D-GuidedGradCAM-for-Medical-Imaging
This Repo containes the implemnetation of generating Guided-GradCAM for 3D medical Imaging using Nifti file in tensorflow 2.0. Different input files can be used in that case need to edit the input to the Guided-gradCAM model.
Stars: ✭ 60 (-25.93%)
Mutual labels:  explainable-ai
responsible-ai-toolbox
This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.
Stars: ✭ 615 (+659.26%)
Mutual labels:  explainable-ai
quadruped control
Quadruped control architecture
Stars: ✭ 46 (-43.21%)
Mutual labels:  planning
LogDensityProblems.jl
A common framework for implementing and using log densities for inference.
Stars: ✭ 26 (-67.9%)
Mutual labels:  bayesian
BrainSimII
Neural Simulator for AGI research and development
Stars: ✭ 51 (-37.04%)
bayesian
Bindings for Bayesian TidyModels
Stars: ✭ 33 (-59.26%)
Mutual labels:  bayesian
XAIatERUM2020
Workshop: Explanation and exploration of machine learning models with R and DALEX at eRum 2020
Stars: ✭ 52 (-35.8%)
Mutual labels:  explainable-ai
MultiBUGS
Multi-core BUGS for fast Bayesian inference of large hierarchical models
Stars: ✭ 28 (-65.43%)
Mutual labels:  bayesian
meg
Molecular Explanation Generator
Stars: ✭ 14 (-82.72%)
Mutual labels:  explainable-ai
urban-and-regional-planning-resources
Community list of data & technology resources concerning the built environment and communities. 🏙️🌳🚌🚦🗺️
Stars: ✭ 109 (+34.57%)
Mutual labels:  planning
Analogy.LogViewer
A customizable Log Viewer with ability to create custom providers. Can be used with C#, C++, Python, Java and others
Stars: ✭ 172 (+112.35%)
Mutual labels:  analogy
Awesome-Vision-Transformer-Collection
Variants of Vision Transformer and its downstream tasks
Stars: ✭ 124 (+53.09%)
Mutual labels:  explainable-ai
ArviZ.jl
Exploratory analysis of Bayesian models with Julia
Stars: ✭ 67 (-17.28%)
Mutual labels:  bayesian
bnp
Bayesian nonparametric models for python
Stars: ✭ 17 (-79.01%)
Mutual labels:  bayesian
1-60 of 167 similar projects