References in zbMATH (referenced in 10 articles )

Showing results 1 to 10 of 10.
Sorted by year (citations)

  1. Paul Scherer, Thomas Gaudelet, Alison Pouplin, Suraj M S, Jyothish Soman, Lindsay Edwards, Jake P. Taylor-King: PyRelationAL: A Library for Active Learning Research and Development (2022) arXiv
  2. Samet Akcay, Dick Ameln, Ashwin Vaidya, Barath Lakshmanan, Nilesh Ahuja, Utku Genc: Anomalib: A Deep Learning Library for Anomaly Detection (2022) arXiv
  3. Yeonghyeon Lee, Kangwook Jang, Jahyun Goo, Youngmoon Jung, Hoirin Kim: FitHuBERT: Going Thinner and Deeper for Knowledge Distillation of Speech Self-Supervised Learning (2022) arXiv
  4. Haiping Lu, Xianyuan Liu, Robert Turner, Peizhen Bai, Raivo E Koot, Shuo Zhou, Mustafa Chasmai, Lawrence Schobs: PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python (2021) arXiv
  5. Haoqi Fan, Tullie Murrell, Heng Wang, Kalyan Vasudev Alwala, Yanghao Li, Yilei Li, Bo Xiong, Nikhila Ravi, Meng Li, Haichuan Yang, Jitendra Malik, Ross Girshick, Matt Feiszli, Aaron Adcock, Wan-Yen Lo, Christoph Feichtenhofer: PyTorchVideo: A Deep Learning Library for Video Understanding (2021) arXiv
  6. Karn N. Watcharasupat, Junyoung Lee, Alexander Lerch: Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models (2021) arXiv
  7. Mirco Ravanelli; Titouan Parcollet; et al: SpeechBrain: A General-Purpose Speech Toolkit (2021) arXiv
  8. Stanziola, Antonio; Arridge, Simon R.; Cox, Ben T.; Treeby, Bradley E.: A Helmholtz equation solver using unsupervised learning: application to transcranial ultrasound (2021)
  9. Victor G. Turrisi da Costa, Enrico Fini, Moin Nabi, Nicu Sebe, Elisa Ricci: Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning (2021) arXiv
  10. Michael Poli, Stefano Massaroli, Atsushi Yamashita, Hajime Asama, Jinkyoo Park: TorchDyn: A Neural Differential Equations Library (2020) arXiv