Generative Data Intelligence

Tag: ICLR

The Best NLP Papers From ICLR 2020

I went through 687 papers that were accepted to ICLR 2020 virtual conference (out of 2594 submitted  –  up 63% since 2019!) and identified 9 papers with the potential to advance the use of deep learning NLP models in everyday use cases. Here are the papers found and why they matter.   ELECTRA: Pre-training Text […]

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Proceedings of the ICLR Workshop on Computer Vision for Agriculture (CV4A) 2020. (arXiv:2004.11051v2 [cs.CV] UPDATED)

No PDF available, click to view other formats Abstract: This is the proceedings of the Computer Vision for...

Proceedings of the ICLR Workshop on Computer Vision for Agriculture (CV4A) 2020. (arXiv:2004.11051v1 [cs.CV])

No PDF available, click to view other formats Abstract: This is the proceedings of the Computer Vision for...

Exclusive Talk with Vijay Krishnan, Founder & CTO of Turing

-Advertisement- Asif: Tell us about your journey in AI/Data Science leading up to this point. Vijay: I have been working in AI...

Attention For Time Series Forecasting And Classification

Transformers (specifically self-attention) have powered significant recent progress in NLP. They have enabled models like BERT, GPT-2, and XLNet to form powerful language...

TensorFlow gets its quantum of solace, lid lifted on ‘all-seeing crime-detecting’ AI upstart, and more

Plus: Machine-learning software scans ancient texts Roundup Here's a handy little roundup of all the bits of AI news that you may have...

How the coronavirus may reshape AI research conferences

COVID-19 officially became a global pandemic on Wednesday. As public health officials and governments respond; businesses brace for losses; and events...

Navigating with grid-like representations in artificial agents

More broadly, our work reaffirms the potential of utilising algorithms thought to be used by the brain as inspiration for machine learning architectures....

DeepMind papers at ICLR 2018

Maximum a posteriori policy optimisationAuthors: Abbas Abdolmaleki, Jost Tobias Springenberg, Nicolas Heess, Yuval Tassa, Remi MunosWe introduce a new algorithm for reinforcement learning...

DeepMind Papers @ NIPS (Part 1)

Interaction Networks for Learning about Objects, Relations and PhysicsAuthors: Peter Battaglia, Razvan Pascanu, Matthew Lai, Danilo Rezende, Koray KavukcuogluReasoning about objects, relations, and...

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