Stars
RootCLAM: On Root Cause Localization and Anomaly Mitigation through Causal Inference (CIKM 2023)
[TKDE 2022] The official PyTorch implementation of the paper "Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs".
000Justin000 / torchdiffeq
Forked from rtqichen/torchdiffeqDifferentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.
few-shot models for short-term traffic prediction
Visualizer for neural network, deep learning and machine learning models
Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).
wcc961129 / transdim
Forked from xinychen/transdimMachine learning for transportation data imputation and prediction.
Graph Neural Networks with Keras and Tensorflow 2.
A library for scientific machine learning and physics-informed learning
The code for GCN, GAT and Graphsage based on pytorch.
It contains the code for the paper Deep Adaptive Wavelet Network
Neural network layer code to implement wavelet deconvolutions
Python Implementation of Reinforcement Learning: An Introduction
apply sugiyama layered graph algorithm to set node position for a graph
Easy to use es rest api, the wrapper of elasticsearch-rest-high-level-client and Jest API, including the custom filter module to compatible with different version of es.
Learning Scheduling Algorithms for Data Processing Clusters
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning
Models and examples built with TensorFlow
Library to implement graph neural networks in PyTorch
Semi-supervised learning with graph embeddings
Collaging on Internal Representations: An Intuitive Approach for Semantic Transfiguration