jianwuwang

jianwuwang's Stars

• lixin4ever/Conference-Acceptance-Rate

  Acceptance rates for the major AI conferences

  Language:Jupyter Notebook4k287

• ReproModel/repromodel

  Boosting the AI research efficiency

  Language:Python341

• Jack-bo1220/Awesome-Remote-Sensing-Foundation-Models

  66066

• nsf-open/nsf-proposal-latex-samples

  LaTeX samples for NSF Research.gov Proposal Submission. For more information about Research.gov Proposal Submission visit https://www.research.gov/research-web/content/aboutpsm Feedback syee@nsf.gov

  Language:TeX20353

• SJ001/AI-Feynman

  Language:Python608186

• divelab/AIRS

  Artificial Intelligence Research for Science (AIRS)

  Language:Python44957

• kochbj/Deep-Learning-for-Causal-Inference

  Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2.

  28165

• kuiy/CausalFS

  An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)

  589

• mlcommons/science

  https://mlcommons.org/en/groups/research-science/

  Language:Jupyter Notebook103

• py-why/causal-learn

  Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

  Language:Python1k174

• interpretml/interpret

  Fit interpretable models. Explain blackbox machine learning.

  Language:C++6.1k723

• big-data-lab-umbc/sea-ice-prediction

  Language:Jupyter Notebook134

• cmu-phil/example-causal-datasets

  Example causal datasets with consistent formatting and ground truth

  5611

• lmcinnes/umap

  Uniform Manifold Approximation and Projection

  Language:Python7.2k784

• vanderschaarlab/mlforhealthlabpub

  Machine Learning and Artificial Intelligence for Medicine.

  Language:Python410167

• NVIDIA-AI-IOT/deepstream_python_apps

  DeepStream SDK Python bindings and sample applications

  Language:Jupyter Notebook1.4k465

• mseitzer/srgan

  Pytorch implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

  Language:Python4214

• ESIPFed/Awesome-Earth-Artificial-Intelligence

  A curated list of Earth Science's Artificial Intelligence (AI) tutorials, notebooks, software, datasets, courses, books, video lectures and papers. Contributions most welcome.

  19047

• big-data-lab-umbc/Reproducible_and_portable_app_in_cloud

  A toolkit to deploy, execute, analyze, and reproduce big data analytics automatically in the cloud.

  Language:Python66

• big-data-lab-umbc/Causality_Discovery_as_a_Service

  Language:Python11

• big-data-lab-umbc/aws-automation

  Language:Jupyter Notebook51

• remicres/sr4rs

  Super resolution for remote sensing

  Language:Python15619

• bradyneal/causal-book-code

  Language:Python7319

• jakevdp/PythonDataScienceHandbook

  Python Data Science Handbook: full text in Jupyter Notebooks

  Language:Jupyter Notebook42k17.7k

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook22.1k3.2k

• janishar/mit-deep-learning-book-pdf

  MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

  Language:Java12.5k2.7k

• probml/pml-book

  "Probabilistic Machine Learning" - a book series by Kevin Murphy

  Language:Jupyter Notebook4.8k577

• jadore801120/attention-is-all-you-need-pytorch

  A PyTorch implementation of the Transformer model in "Attention is All You Need".

  Language:Python8.6k2k

• M-Nauta/TCDF

  Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

  Language:Jupyter Notebook456101

• aymericdamien/TopDeepLearning

  A list of popular github projects related to deep learning

  Language:Python5.8k1.2k