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microsoft / dowhy
Python 0 0
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
machine-learning data-science causal-inference causality treatment-effects bayesian-networks causal-machine-learning causal-models do-calculus graphical-models python3
Обновлено 2024-11-22 19:51:17 +03:00
microsoft / hummingbird
Python 0 0
Hummingbird compiles trained ML models into tensor computation for faster inference.
machine-learning pytorch neural-networks scikit-learn tensor-computation
Обновлено 2024-11-16 00:52:33 +03:00
microsoft / graspologic
Python 0 0
Python package for graph statistics
machine-learning python data-science graph graph-statistics networks
Обновлено 2024-10-09 19:41:04 +03:00
microsoft / topologic
Python 0 0
A python library for intelligently building networks and network embeddings, and for analyzing connected data.
Обновлено 2024-07-11 21:49:18 +03:00
microsoft / tf2-gnn
Python 0 0
TensorFlow 2 library implementing Graph Neural Networks
Обновлено 2023-07-13 16:47:00 +03:00
microsoft / MT-DNN
Python 0 0
Multi-Task Deep Neural Networks for Natural Language Understanding
natural-language-processing natural-language-understanding mt-dnn multi-task-learning
Обновлено 2023-06-13 00:28:35 +03:00
microsoft / Relation-Aware-Global-Attention-Networks
Python 0 0
We design an effective Relation-Aware Global Attention (RGA) module for CNNs to globally infer the attention.
Обновлено 2023-06-12 21:55:25 +03:00
microsoft / View-Adaptive-Neural-Networks-for-Skeleton-based-Human-Action-Recognition
Python 0 0
View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition
Обновлено 2023-06-12 21:55:25 +03:00
microsoft / tf-gnn-samples
Python 0 0
TensorFlow implementations of Graph Neural Networks
Обновлено 2022-11-28 22:09:39 +03:00
microsoft / conservative-uncertainty-estimation-random-priors
Python 0 0
Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)
Обновлено 2022-11-28 22:09:08 +03:00
microsoft / LQ-Nets
Python 0 0
LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks
dnn cnn compression quantization
Обновлено 2022-08-30 11:00:20 +03:00
microsoft / ptgnn
Python 0 0
A PyTorch Graph Neural Network Library
deep-learning pytorch geometric-deep-learning gnn graph-neural-networks
Обновлено 2022-02-01 20:31:29 +03:00
microsoft / seismic-deeplearning
Python 0 0
Deep Learning for Seismic Imaging and Interpretation
microsoft deep-learning computer-vision neural-networks segmentation seismic-processing seismic seismic-data seismic-imaging seismic-inversion
Обновлено 2020-09-19 01:18:20 +03:00
microsoft / SGN
Python 0 0
This is the implementation of CVPR2020 paper “Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition”.
Обновлено 2020-04-17 10:08:50 +03:00
microsoft / Recursive-Cascaded-Networks
Python 0 0
[ICCV 2019] Recursive Cascaded Networks for Unsupervised Medical Image Registration
unsupervised-learning iccv2019 medical-image-registration
Обновлено 2019-12-08 09:48:23 +03:00
microsoft / gated-graph-neural-network-samples
Python 0 0
Sample Code for Gated Graph Neural Networks
Обновлено 2019-10-10 12:27:15 +03:00
Unity-Technologies / Keras-GAN
Python 0 0
Keras implementations of Generative Adversarial Networks.
Обновлено 2019-09-13 17:32:32 +03:00