Fetching the paper…
Reading the bibliography…
Recent advances in neural forecasting have produced major improvements in accuracy for probabilistic demand prediction.
Attention, please! a critical review of neural attention models in natural language processing
Galassi, A · 1902
Earlier work this paper cites.
Financial series prediction using Attention LSTM
Kim, S · 1902
Earlier work this paper cites.
Deep Learning for Time Series Forecasting: The Electric Load Case
Gasparin, A · 1907
Earlier work this paper cites.
Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting
Lim, B · 1912
Earlier work this paper cites.
STConvS2S: Spatiotemporal Convolutional Sequence to Sequence Network for weather forecasting
Nascimento, R. C · 1912
Earlier work this paper cites.
Probability with Martingales
Williams, D · 1991
Earlier work this paper cites.
Modeling the evolution of demand forecasts with application to safety stock analysis in production/distribution systems
Heath, D. C · 1994
Earlier work this paper cites.
Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information
Chen, F · 2000
Earlier work this paper cites.
Neural forecasting: Introduction and literature overview
Benidis, K · 2004
Earlier work this paper cites.
Oxford-man institute’s realized library
Gerd Heber, N. S., Asger Lunde · 2009
Earlier work this paper cites.
Information Transmission and the Bullwhip Effect: An Empirical Investigation
Bray, R. L · 2012
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Bahdanau, D · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Sutskever, I · 2014
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
Kingma, D. P · 2015
Cited alongside, same era.
Effective approaches to attention-based neural machine translation
Luong, M.-T · 2015
Cited alongside, same era.
Show, attend and tell: Neural image caption generation with visual attention
Xu, K · 2015
Cited alongside, same era.
Long short-term memory-networks for machine reading
Cheng, J · 2016
Cited alongside, same era.
Wavenet: A generative model for raw audio
van den Oord, A · 2016
Cited alongside, same era.
Self-Attention with Relative Position Representations
Shaw, P · 2018
Later among the works it cites.
Election predictions as martingales: an arbitrage approach
Taleb, N. N · 2018
Later among the works it cites.
Belief movement, uncertainty reduction, and rational updating
Augenblick, N · 2019
Later among the works it cites.
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
Dai, Z · 2019
Later among the works it cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J · 2019
Later among the works it cites.
Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting
Li, S · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cinar, Y. G · 2017
Cited alongside, same era.
UCI machine learning repository. URL http://archive.ics.uci.edu/ml
Dua, D · 2017
Cited alongside, same era.
Attention is all you need
Vaswani, A · 2017
Cited alongside, same era.
A multi-horizon quantile recurrent forecaster
Wen, R · 2017
Cited alongside, same era.
Long-term Forecasting using Higher Order Tensor RNNs
Yu, R · 2017
Cited alongside, same era.
Music Transformer: Generating Music with Long-Term Structure
Huang, C.-Z. A · 2018
Cited alongside, same era.
Sample path generation for probabilistic demand forecasting
Madeka, D · 2018
Cited alongside, same era.
Sequence to sequence deep learning models for solar irradiation forecasting
Mukhoty, B. P · 2019
Later among the works it cites.
Temporal pattern attention for multivariate time series forecasting
Shun-Yao Shih and Fan-Keng Sun and Hung-yi Lee · 2019
Later among the works it cites.
All roads lead to quantitative finance
Taleb, N. N · 2019
Later among the works it cites.
Deep Generative Quantile-Copula Models for Probabilistic Forecasting
Wen, R · 2019
Later among the works it cites.
Deepar: Probabilistic forecasting with autoregressive recurrent networks
Salinas, D · 2020
Closest in time.
Threshold Martingales and the Evolution of Forecasts
Foster, D · 2021
Closest in time.