attention_to_gif
Informer2020
| attention_to_gif | Informer2020 | |
|---|---|---|
| 1 | 2 | |
| 1 | 4,936 | |
| - | - | |
| 4.4 | 0.6 | |
| about 3 years ago | 2 months ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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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.
attention_to_gif
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[P] attention_to_gif: Visualizing The Transition of Attention In BERT as a GIF
[Colab Link] [Github Code Link]
Informer2020
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[R] Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Code for https://arxiv.org/abs/2012.07436 found: https://github.com/zhouhaoyi/Informer2020
- [R][D] Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting. Zhou et al. AAAI21 Best Paper. ProbSparse self-attention reduces complexity to O(nlogn), generative style decoder to obtainsequence output in one step, and self-attention distilling for further reducing memory
What are some alternatives?
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
pytorch-forecasting - Time series forecasting with PyTorch
how-do-vits-work - (ICLR 2022 Spotlight) Official PyTorch implementation of "How Do Vision Transformers Work?"
neural_prophet - NeuralProphet: A simple forecasting package
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).
long-range-arena - Long Range Arena for Benchmarking Efficient Transformers
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