NIPS 2017 – Deep Hunt

This year's Neural Information Processing Systems (NIPS) 2017 conference held at Long Beach Convention Center, Long Beach California has been the biggest ever! Here's a list of resources and slides of all invited talks, tutorials and workshops.

NIPS 2017

This list is still incomplete and will be regularly updated. Contributions are welcome. You can add links via pull requests or create an issue in the Github Repo to lemme know something I missed or to start a discussion. If you know the speakers, please ask them to upload slides online!

Invited Talks

  • Powering the next 100 years, John Platt
  • Why AI Will Make it Possible to Reprogram the Human Genome, Brendan J Frey
  • The Trouble with Bias, Kate Crawford
  • The Unreasonable Effectiveness of Structure, John Platt
  • Deep Learning for Robotics, Pieter Abbeel
  • Learning State Representations, Yael Niv
  • On Bayesian Deep Learning and Deep Bayesian Learning, Yee Whye Teh




  • Bayesian machine learning: Quantifying uncertainty and robustness at scale, Tamara​ ​Broderick​
  • Towards Communication-Centric Multi-Agent Deep Reinforcement Learning for Guarding a Territory, Aishwarya​ ​Unnikrishnan
  • Graph convolutional networks can encode three-dimensional genome architecture in deep learning models for genomics, Peyton​ ​Greenside​
  • Machine Learning for Social Science, Hannah​ ​Wallach​
  • Fairness Aware Recommendations, Palak​ ​Agarwal​
  • Reinforcement Learning with a Corrupted Reward Channel, Victoria​ ​Krakivna​
  • Improving health-care: challenges and opportunities for reinforcement learning, Joelle​ ​Pineau​
  • Harnessing Adversarial Attacks on Deep Reinforement Learning for Improving Robustness, Zhenyi​ ​Tang​
  • Time-Critical Machine Learning, Nina​ ​Mishra​
  • A General Framework for Evaluating Callout Mechanisms in Repeated Auctions, Hoda​ ​Heidari​
  • Engaging Experts: A Dirichlet Process Approach to Divergent Elicited Priors in Social Science, Sarah​ ​Bouchat​
  • Representation Learning in Large Attributed Graphs, Nesreen​ ​K​ ​Ahmed​

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