⏰ AI conference deadline countdowns

2024届互联网校招信息汇总

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

A parallel ODE solver for PyTorch

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

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

Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations

Quickly bring up your PyTorch project(a skeleton)

Gitbook based Blog, Android, Linux, Deep Learning, Computer Vision

Graph Neural Networks for Irregular Time Series

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

Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.

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

"Graph Neural Controlled Differential Equations for Traffic Forecasting", AAAI 2022

Experiments for Neural Flows paper

Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight

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）

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

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

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

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

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

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

Neural Graph Differential Equations (Neural GDEs)