I think 70% of our anxieties about modern technology can be traced back to Western governments transfering big chunks of R&D and expertise from public sector to private sector, which develops things in different ways with different priorities— Jack Clark (@jackclarkSF) December 8, 2019
DGL (Deep Graph Library) –clean abstraction for building graph-based neural nets atop PyTorch/MxNet. Comes pre-built with auto-batching, sparse-multiplication and 10 different models like GCNs or TreeLSTM— ML Review (@ml_review) December 7, 2019
Happy Birthday 🎂🎈🎉 pic.twitter.com/K2IoHawsez
Our team will be presenting Novograd at Beyond First Order Methods in ML and NeMo at MLSys workshops.— Chip Huyen @ NeurIPS (@chipro) December 7, 2019
I'll be on a panel with some academic heroes of mine to discuss research vs industry at NewInML, 3pm Monday.
Hit me up if you want to chat! #NeurIPS2019https://t.co/WHzcfh7pG0
How does transfer learning for medical imaging affect performance, representations and convergence? In a new #NeurIPS2019 paper, we investigate this across different architectures and datasets, finding some surprising conclusions! Learn more below: https://t.co/svZY5sUJEu— Google AI (@GoogleAI) December 6, 2019