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TBhacker's Projects

ancde icon ancde

Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting

astgnn icon astgnn

This is a Pytorch implementation of ASTGNN. Now the corresponding paper is available online at https://ieeexplore.ieee.org/document/9346058.

cvpr_dnri icon cvpr_dnri

Code accompanying "Dynamic Neural Relational Inference" from CVPR 2020

diffrax icon diffrax

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable.

dlinear icon dlinear

This is an official implementation for "Are Transformers Effective for Time Series Forecasting?"

fasterneuraldiffeq icon fasterneuraldiffeq

Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)

gde icon gde

Neural Graph Differential Equations (Neural GDEs)

it_book icon it_book

本项目收藏这些年来看过或者听过的一些不错的常用的上千本书籍,没准你想找的书就在这里呢,包含了互联网行业大多数书籍和面试经验题目等等。有人工智能系列(常用深度学习框架TensorFlow、pytorch、keras。NLP、机器学习,深度学习等等),大数据系列(Spark,Hadoop,Scala,kafka等),程序员必修系列(C、C++、java、数据结构、linux,设计模式、数据库等等)

latent_ode icon latent_ode

Code for "Latent ODEs for Irregularly-Sampled Time Series" paper

mtan icon mtan

Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.

neural-ode icon neural-ode

Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations

neuralcde icon neuralcde

Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)

neurallaplace icon neurallaplace

Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.

neuralrdes icon neuralrdes

Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)

pdformer icon pdformer

[AAAI2023] A PyTorch implementation of PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction.

raindrop icon raindrop

Graph Neural Networks for Irregular Time Series

snopt icon snopt

Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight

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