mlsanityData to 7 Oct 2026

Continual Inference: A Library for Efficient Online Inference with Deep Neural Networks in PyTorch

arXiv 2204.03418 ↗First posted 7 Apr 2022cs.LG cs.AIcited by 8

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Abstract (arXiv)

We present Continual Inference, a Python library for implementing Continual Inference Networks (CINs) in PyTorch, a class of Neural Networks designed specifically for efficient inference in both online and batch processing scenarios. We offer a comprehensive introduction and guide to CINs and their implementation in practice, and provide best-practices and code examples for composing complex modules for modern Deep Learning. Continual Inference is readily downloadable via the Python Package Index and at urlwww.github.com/lukashedegaard/continual-inference.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 14 of its 21 references that are in the map. First posted on arXiv 7 Apr 2022.

Builds on

14 of 21 references.

References · 14

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  4. 2014Going Deeper with Convolutionscited by 4,231
  5. 2017Quo Vadis, Action Recognition? A New Model and the Kinetics Datasetcited by 3,259
  6. 2018SlowFast Networks for Video Recognitioncited by 1,862
  7. 2014On the Properties of Neural Machine Translation: Encoder-Decoder Approachescited by 1,303
  8. 2018Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognitioncited by 1,199
  9. 2020X3D: Expanding Architectures for Efficient Video Recognitioncited by 635
  10. 2020Skeleton-based Action Recognition via Spatial and Temporal Transformer Networkscited by 98
  11. 2015Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Videocited by 15
  12. 2022Continual Transformers: Redundancy-Free Attention for Online Inferencecited by 12
2 more
  1. 2021Continual 3D Convolutional Neural Networks for Real-time Processing of Videoscited by 9
  2. 2020Dissected 3D CNNs: Temporal Skip Connections for Efficient Online Video Processingcited by 5

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 5.

8 papers.

  1. 2022Efficient High-Resolution Deep Learning: A Surveycited by 9
  2. 2025Real-Time Streamable Generative Speech Restoration with Flow Matchingcited by 4
  3. 2024Continual Low-Rank Scaled Dot-product Attentioncited by 2
  4. 2025LOBERT: Generative AI Foundation Model for Limit Order Book Messagescited by 2
  5. 2025Online hand gesture recognition using Continual Graph Transformerscited by 1
  6. 2025Real-Time Streaming Mel Vocoding with Generative Flow Matchingcited by 1
  7. 2023Efficient Online Processing with Deep Neural Networkscited by 0
  8. 2025DeepCoT: Deep Continual Transformers for Real-Time Inference on Data Streamscited by 0