└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # NIPS 2017 Links 2 | 3 | ## Monday (Tutorials) 4 | 5 | [A Primer on Optimal Transport](https://www.dropbox.com/s/ct3500ko00i5sz3/aprimeronOT.m4v?dl=0) ([slides](https://www.dropbox.com/s/55tb2cf3zipl6xu/aprimeronOT.pdf?dl=0)) 6 | [Deep Learning: Practice and Trends](https://www.youtube.com/watch?v=YJnddoa8sHk) 7 | [Reinforcement Learning with People](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1555771847847382%2F&show_text=0&width=560) 8 | [Fairness in Machine Learning](http://mrtz.org/nips17/#/) 9 | [Statistical Relational Artificial Intelligence: Logic, Probability and Computation](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1552222671535633%2F&show_text=0&width=560) 10 | [Deep Probabilistic Modelling with Gaussian Processes](https://www.youtube.com/watch?v=NHTGY8VCinY) 11 | [Differentially Private Machine Learning: Theory, Algorithms and Applications](http://www.ece.rutgers.edu/~asarwate/nips2017/) 12 | [Geometric Deep Learning on Graphs and Manifolds](https://www.dropbox.com/s/zdosxw3nc3f1p2r/NIPS-GDL.pdf?dl=0) 13 | [Engineering and Reverse-Engineering Intelligence Using Probabilistic Programs, Program Induction, and Deep Learning](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1552446408179926%2F&show_text=0&width=560) 14 | [Opening Remarks and Powering the next 100 years](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1552610871496813%2F&show_text=0&width=560) 15 | 16 | ## Tuesday (Conference) 17 | 18 | [Invited Talk: Brendan Frey: Why AI Will Make it Possible to Reprogram the Human Genome](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1553236368100930%2F&show_text=0&width=560) 19 | [Test of Time Award](https://www.youtube.com/watch?v=Qi1Yry33TQE) 20 | Parallel Tracks on [Algorithms](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1553335844757649%2F&show_text=0&width=560) and [Optimization](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1553355798088987%2F&show_text=0&width=560) 21 | [Invited Talk: Kate Crawford: The Trouble wih Bias](https://www.youtube.com/watch?v=fMym_BKWQzk) 22 | Parallel Tracks on [Algorithms, Optimization](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1553537531404147%2F&show_text=0&width=560) and [Theory](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1553539891403911%2F&show_text=0&width=560) 23 | Parallel Tracks on [Deep Learning, Applications](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1553634558061111%2F&show_text=0&width=560) and [Algorithms](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1553635538061013%2F&show_text=0&width=560) 24 | 25 | 26 | ## Wednesday (Conference) 27 | 28 | [Invited Talk: Lise Getoor: The Unreasonable Effectiveness of Structure](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1554329184658315%2F&show_text=0&width=560) 29 | Parallel Tracks on [Theory, Probablilistic Methods](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1554402064651027%2F&show_text=0&width=560) [and Deep Learning](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1554402331317667%2F&show_text=0&width=560) 30 | [Invited Talk: Pieter Abbeel: Deep Learning for Robotics](https://www.youtube.com/watch?v=po9z_tMuEwE) 31 | Parallel Tracks on [Reinforcement Learning, Deep Learning](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1554654864625747%2F&show_text=0&width=560) and [Optimization](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1554657104625523%2F&show_text=0&width=560) 32 | Parallel Tracks on [Reinforcement Learning, Algorithms, Applications](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1554741347950432%2F&show_text=0&width=560) and [Probabilistic Methods, Applications](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1554741734617060%2F&show_text=0&width=560) 33 | 34 | ## Thursday (Conference + Symposia) 35 | 36 | [Invited Talk: Yael Niv: Learning State Representations](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1555427447881822%2F&show_text=0&width=560) 37 | [Invited Talk: Yee Whye Teh: On Bayesian Deep Learning and Deep Bayesian Learning](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1555493854541848%2F&show_text=0&width=560) 38 | Parallel Tracks on [Neuroscience](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1555551597869407%2F&show_text=0&width=560) and [Deep Learning, Algorithms](https://www.facebook.com/plugins/video.php?href=https%3A%2F%2Fwww.facebook.com%2Fnipsfoundation%2Fvideos%2F1555553784535855%2F&show_text=0&width=560) 39 | [Interpretable Machine Learning](http://interpretable.ml/) 40 | [Metalearning](http://metalearning-symposium.ml/) 41 | [Deep Reinforcement Learning](https://sites.google.com/view/deeprl-symposium-nips2017/) 42 | [Kinds of intelligence: types, tests and meeting the needs of society](http://kindsofintelligence.org/) 43 | 44 | ## Friday (Workshops see [website](https://nips.cc/Conferences/2017/Schedule?type=Workshop) for homepages) 45 | Conversational AI - today's practice and tomorrow's potential 46 | Learning in the Presence of Strategic Behavior 47 | 6th Workshop on Automated Knowledge Base Construction (AKBC) 48 | Advances in Modeling and Learning Interactions from Complex Data 49 | Visually grounded interaction and language 50 | NIPS 2017 Time Series Workshop 51 | Machine Learning for the Developing World 52 | Machine Deception 53 | Acting and Interacting in the Real World: Challenges in Robot Learning 54 | Nearest Neighbors for Modern Applications with Massive Data: An Age-old Solution with New Challenges 55 | Learning on Distributions, Functions, Graphs and Groups 56 | Machine Learning and Computer Security 57 | Workshop on Worm's Neural Information Processing (WNIP) 58 | Synergies in Geometric Data Analysis (TWO DAYS) 59 | Deep Learning for Physical Sciences 60 | Machine Learning for Audio Signal Processing (ML4Audio) 61 | Machine Learning for Creativity and Design 62 | Transparent and interpretable Machine Learning in Safety Critical Environments 63 | Advances in Approximate Bayesian Inference 64 | OPT 2017: Optimization for Machine Learning 65 | Discrete Structures in Machine Learning 66 | Competition track 67 | ML Systems Workshop @ NIPS 2017 68 | Machine Learning for Molecules and Materials 69 | Extreme Classification: Multi-class & Multi-label Learning in Extremely Large Label Spaces 70 | From 'What If?' To 'What Next?' : Causal Inference and Machine Learning for Intelligent Decision Making 71 | 72 | ## Saturday (Workshops see [website](https://nips.cc/Conferences/2017/Schedule?type=Workshop) for homepages) 73 | Bayesian Deep Learning 74 | Medical Imaging meets NIPS 75 | Machine Learning Challenges as a Research Tool 76 | Deep Learning at Supercomputer Scale 77 | Machine Learning on the Phone and other Consumer Devices 78 | Teaching Machines, Robots, and Humans 79 | Machine Learning in Computational Biology 80 | Learning with Limited Labeled Data: Weak Supervision and Beyond 81 | 2017 NIPS Workshop on Machine Learning for Intelligent Transportation Systems 82 | Hierarchical Reinforcement Learning 83 | Workshop on Meta-Learning 84 | The future of gradient-based machine learning software & techniques 85 | NIPS Highlights (MLTrain), Learn How to code a paper with state of the art frameworks 86 | (Almost) 50 shades of Bayesian Learning: PAC-Bayesian trends and insights 87 | Interpreting, Explaining and Visualizing Deep Learning - Now what ? 88 | Optimal Transport and Machine Learning 89 | BigNeuro 2017: Analyzing brain data from nano to macroscale 90 | Cognitively Informed Artificial Intelligence: Insights From Natural Intelligence 91 | Aligned Artificial Intelligence 92 | Bayesian optimization for science and engineering 93 | Synergies in Geometric Data Analysis (2nd day) 94 | Emergent Communication Workshop 95 | Workshop on Prioritising Online Content 96 | Collaborate & Communicate: An exploration and practical skills workshop that builds on the experience of AIML experts who are both successful collaborators and great communicators. 97 | Learning Disentangled Features: from Perception to Control 98 | Deep Learning: Bridging Theory and Practice 99 | 100 | ## Other: 101 | 102 | [Nvidia](https://www.youtube.com/watch?v=u6N5RAFRGaE) 103 | [Tesla](https://www.youtube.com/watch?v=jBbYU6-r5Us) 104 | --------------------------------------------------------------------------------