The Deep Learning User Group currently operates through a small number of in-person meetings per year. The meetings provide an excellent opportunity to find out what others are doing, exchange tips, learn from lightning talks, and discuss issues with members of Research Computing. Anyone interested in machine learning is welcome to attend. Subscribe to the PICSciE/RC mailing list to receive updates.Be aware of the getting started guides by Princeton Research Computing for PyTorch, JAX and TensorFlow.To volunteer to help with planning and putting on future events, send e-mail to [email protected].The group is sponsored by the Princeton Institute for Computational Science and Engineering (PICSciE) and the Center for Statistics and Machine Learning (CSML). Upcoming meetingMachine Learning and PizzaTuesday, October 22, 2024 at 12:00-1:00 PMJoin your fellow deep learning enthusiasts to discuss all matters of deep learning, get tips from members of Research Computing, and learn about what is going on at Princeton. We will provide updates on PyTorch, JAX and TensorFlow. Previous meetingsMachine Learning and PizzaMarch 2, 2023 at 12:00-1:00 PMJAX: A Machine-Learning Research Library by Peter Hawkins, Google AINovember 7, 2022 at 4:30-5:30 PM.TensorFlow and PizzaOctober 25, 2022 at 12:00-1:00 PMPyTorch and PizzaSeptember 28, 2022 at 12:00-1:00 PMFoundations of Deep Learning with PyTorch, Prof. Alf Canziani, NYUFebruary 2020A Dive in to TensorFlow 2.0 by Josh Gordon, GoogleNovember 2019Leveraging Intel Software Libraries for Accelerated AI Research by Jonathan HalversonContinual adaptation for efficient machine communication by Robert HawkinsAccelerating automated modeling and design with stochastic optimization and neural networks by Alex BeatsonOctober 2019JAX: Accelerated machine learning research via composable function transformations in Python by Peter Hawkins, Google AISeptember 2019Selene: A PyTorch-based Deep Learning Library for Sequence Data by Kathleen ChenBig data of big tissues: deep neural networks to accelerate analysis of collective cell behaviors in large populations by Julienne LaChanceGPU Computing with R and Keras by Danny SimpsonAnnouncements and TensorFlow 2 (beta) by Jonathan HalversonJuly 2019Opportunities and challenges in self-driving cars at NVIDIA by Timur RvachovTraining deep convolutional neural networks by Michael Churchill, PPPLDeep Learning Frameworks at Princeton by Jonathan HalversonJune 2019 ContactFor more information, please send an email to [email protected].
