Informer2020 VS query-selector

Compare Informer2020 vs query-selector and see what are their differences.

Informer2020

The GitHub repository for the paper "Informer" accepted by AAAI 2021. (by zhouhaoyi)

query-selector

LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION (by moraieu)
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Informer2020 query-selector
2 1
4,915 75
- -
0.6 3.7
about 2 months ago 5 months ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Informer2020

Posts with mentions or reviews of Informer2020. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-02-24.

query-selector

Posts with mentions or reviews of query-selector. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Informer2020 and query-selector you can also consider the following projects:

pytorch-forecasting - Time series forecasting with PyTorch

neural_prophet - NeuralProphet: A simple forecasting package

LaTeX-OCR - pix2tex: Using a ViT to convert images of equations into LaTeX code.

DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

sktime - A unified framework for machine learning with time series

SAITS - The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-series imputation (impute multivariate incomplete time series containing NaN missing data/values with machine learning). https://arxiv.org/abs/2202.08516

CrabNet - Predict materials properties using only the composition information!

how-do-vits-work - (ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?"

gluonts - Probabilistic time series modeling in Python