Deep Matching, Correlation and Prediction (DeepMCP) Model

Google Research

[CVPR 2022 Oral] Balanced MSE for Imbalanced Visual Regression https://arxiv.org/abs/2203.16427

[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

A memory-efficient implementation of DenseNets

OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning

Paper list in traffic prediction field

Pytorch Implementation of DeepLGR, ECML-PKDD-20

[ICLR2022] official implementation of UniFormer

This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the …

DMVST-Net for AAAI 2018

Codes for AAAI 2019 DeepSTN+: Context-aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis

Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method

40GB LTE datasets of raw signals collect in shielding box

Data and source code of paper "Analyzing and Modeling Spatio-Temporal Dependence of Cellular Traffic at City Scale", ICC 2015

PyTorch code for CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting (ICLR 2022)

Code snippets of ST-ResNet by PyTorch

Data, Benchmarks, and methods submitted to the M5 forecasting competition

Code for our SIGKDD'22 paper Pre-training-Enhanced Spatial-Temporal Graph Neural Network For Multivariate Time Series Forecasting.

[ACL 2023] Code for paper “Tailoring Instructions to Student’s Learning Levels Boosts Knowledge Distillation”(https://arxiv.org/abs/2305.09651)

[GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)

Self-supervised contrastive learning for time series via time-frequency consistency

Pytorch implementation of Self-Attention ConvLSTM

Self-Attention ConvLSTM for Spatiotemporal Prediction, described in `https://ojs.aaai.org//index.php/AAAI/article/view/6819`, test on MovingMNIST.

AAAI 2020. Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting

Codes for a WWW'21 Paper. POI recommender system for location/trajectory prediction.

Implementation of Convolutional LSTM in PyTorch.

PyTorch implementations of several SOTA backbone deep neural networks (such as ResNet, ResNeXt, RegNet) on one-dimensional (1D) signal/time-series data.