January 15, 2020
PyTorch 1.4 released, domain libraries updated
Today, we’re announcing the availability of PyTorch 1.4, along with updates to the PyTorch domain libraries. These releases build on top of the announcements from NeurIPS 2019, where we shared the availability of PyTorch Elastic, a new classification framework for image and video, and the addition of Preferred Networks to the PyTorch community. For those that attended the ...
December 06, 2019
PyTorch adds new tools and libraries, welcomes Preferred Networks to its community
PyTorch continues to be used for the latest state-of-the-art research on display at the NeurIPS conference next week, making up nearly 70% of papers that cite a framework. In addition, we’re excited to welcome Preferred Networks, the maintainers of the Chainer framework, to the PyTorch community. Their teams are moving fully over to PyTorch for developing their ML capabilities and services.
December 06, 2019
OpenMined and PyTorch partner to launch fellowship funding for privacy-preserving ML community
Many applications of machine learning (ML) pose a range of security and privacy challenges.
October 10, 2019
PyTorch 1.3 adds mobile, privacy, quantization, and named tensors
PyTorch continues to gain momentum because of its focus on meeting the needs of researchers, its streamlined workflow for production use, and most of all because of the enthusiastic support it has received from the AI community. PyTorch citations in papers on ArXiv grew 194 percent in the first half of 2019 alone, as noted by O...
August 08, 2019
New Releases: PyTorch 1.2, torchtext 0.4, torchaudio 0.3, and torchvision 0.4
Since the release of PyTorch 1.0, we’ve seen the community expand to add new tools, contribute to a growing set of models available in the PyTorch Hub, and continually increase usage in both research and production.
July 23, 2019
Mapillary Research: Seamless Scene Segmentation and In-Place Activated BatchNorm
With roads in developed countries like the US changing up to 15% annually, Mapillary addresses a growing demand for keeping maps updated by combining images from any camera into a 3D visualization of the world. Mapillary’s independent and collaborative approach enables anyone to collect, share, and use street-level images for improving maps, developing cities, and advancing the automotive industry.
July 18, 2019
PyTorch Adds New Ecosystem Projects for Encrypted AI and Quantum Computing, Expands PyTorch Hub
The PyTorch ecosystem includes projects, tools, models and libraries from a broad community of researchers in academia and industry, application developers, and ML engineers. The goal of this ecosystem is to support, accelerate, and aid in your exploration with PyTorch and help you push the state of the art, no matter what field you are exploring. Similarly, we are expanding the recently launched PyTorch Hub to further help you discover and reproduce the latest research.
June 10, 2019
Towards Reproducible Research with PyTorch Hub
Reproducibility is an essential requirement for many fields of research including those based on machine learning techniques. However, many machine learning publications are either not reproducible or are difficult to reproduce. With the continued growth in the number of research publications, including tens of thousands of papers now hosted on arXiv and submissions to conferences at an all time high, research reproducibility is more important than ever. While many of these publications are a...
