crystal22,github

thacil-1

Temporal Hierarchical Attention at Category- and Item-Level for Micro-Video Click-Through Prediction

tida-gcn

Implementation of "Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendation" (TNNLs 2022)

time-attention

n from the paper https://arxiv.org/abs/1704.02971

time-aware-location-prediction

[TKDE 2022] Time-Aware Location Prediction by Convolutional Area-of-Interest Modeling and Memory-Augmented Attentive LSTM

time-series-prediction

A collection of time series prediction methods: rnn, seq2seq, cnn, wavenet, transformer, unet, n-beats, gan, kalman-filter

time-series-works-conferences

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, etc.)

tisasrec

TensorFlow implementation for paper Time Interval Aware Self-Attention for Sequential Recommendation.

In this research, we present a problem of queuing time aware next POI recommendation and demonstrate how it is non-trivial to both recommend a next POI and simultaneously predict its queuing time. To solve this problem, we propose a multi-task, multi head attention transformer model called TLR-M. The model recommends next POIs to the target users and predicts queuing time to access the POIs simultaneously. By utilizing multi-head attention, the TLR-M model can integrate long range dependencies between any two POI visit efficiently and evaluate their contribution to select next POIs and to predict queuing time. To use this code in your research work please cite the following paper. Sajal Halder, Kwan Hui Lim, Jeﬀrey Chan, and Xiuzhen Zhang. Transformer-based multi-task learning for queuing time aware next poi recommendation. In Paciﬁc-Asia Conference on Knowledge Discovery and Data Mining, pages 510–523. Springer, 2021, DOI: https://doi.org/10.1007/978-3-030-75765-6_41

tmca

Code For Next Point-of-Interest Recommendation with Temporal and Multi-level Context Attention

tmer

topic-enhanced-memory-networks-for-personalised-point-of-interest-recommendation

KDD2019

totsnyc

totsNYC

tpa-lstm

Attention Mechanism for Multivariate Time Series Forecasting

tpg

CIKM'2023 official implementation code

traffic-prediction-open-code-summary

Summary of open source code for deep learning models in the field of traffic prediction

traffic-sign-detection

Real-time traffic sign detection using Gielis curves

trafficflowforecasting

Some TrafficFlowForecasting Solutions(交通流量预测解决方案)

traffic_prediction

Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).