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Rotation, Translation, and Cropping for Zero-Shot Generalization Makes a lot of sense. Try playing Doom not from an agent-centric perspective! I think agent-centric view is a better prior for encoding useful information using fewer bits for the policy. https://arxiv.org/abs/2001.09908 https://twitter.com/togelius/status/1223403839354822656 …pic.twitter.com/OfxGrWgKWO
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Quaternions and Euler angles are discontinuous and difficult for neural networks to learn. They show 3D rotations have continuous representations in 5D and 6D, which are more suitable for learning. i.e. regress two vectors and apply Graham-Schmidt (GS). https://arxiv.org/abs/1812.07035 pic.twitter.com/fXUF3sgkTT
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We released the code and data for GraspNet paper (https://arxiv.org/abs/1905.10520 ). Code and data can be found at https://github.com/NVlabs/6dof-graspnet ….https://youtu.be/jypErPo47IA
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TRADI: Tracking deep neural network weight distributions -- work with G. Franchi https://arxiv.org/abs/1912.11316 We’re proposing a cheap method for getting ensembles of networks from a single network training 1/pic.twitter.com/J31E9aaiKL
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Teaching Deep Unsupervised Learning (2nd edition) at
@UCBerkeley this semester. You can follow along here: https://sites.google.com/view/berkeley-cs294-158-sp20/home … Instructor Team:@peterxichen ,@Aravind7694 ,@hojonathanho , Wilson Yan, Alex Li,@pabbeel YouTube, PDF, and Google Slides for ease of re-usepic.twitter.com/VTvffsEjHf
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Facebook AI has effectively solved the task of point-goal navigation by AI agents in simulated environments, using only a camera, GPS, and compass data. Agents achieve 99.9% success in a variety of virtual settings, such as houses and offices. https://ai.facebook.com/blog/near-perfect-point-goal-navigation-from-25-billion-frames-of-experience/ …pic.twitter.com/Cogyp90CwW
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Every 1-2 months, "QT-Opt grasping" paper authors receive an email asking about implementation details of the convnet. Took awhile, but we finally got around to open-sourcing the QT-Opt model as a Tensor2Robot model.https://github.com/google-research/tensor2robot/tree/master/research/qtopt …
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Q-learning is difficult to apply when the number of available actions is large. We show that a simple extension based on amortized stochastic search allows Q-learning to scale to high-dimensional discrete, continuous or hybrid action spaces: https://arxiv.org/abs/2001.08116
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Great coverage by
@Kyle_L_Wiggers in@venturebeat regarding our recent work on effective treatment of hybrid problems with discrete-continuous action spaces in their native form (imagine e.g. controlling gears and gas in your car).https://venturebeat.com/2020/01/06/deepmind-researchers-introduce-hybrid-solution-to-robot-control-problems/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Today, we open-sourced our Spot software development kit and announced our first-ever user conference Actuate! Learn more about what users like
@donttrythis and@testedcom are doing with Spot's SDK on our blog: https://www.bostondynamics.com/01-23-2020 See the full video: https://youtu.be/k7s1sr4JdlI pic.twitter.com/cnIjMvSFIQHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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We have two papers on learning keypoint representations for robot manipulation accepted in
#ICRA2020. 6-PACK: Category-level 6D Pose Tracker with Anchor-Based Keypoints https://sites.google.com/view/6packtracking … KETO: Learning Keypoint Representations for Tool Manipulationhttps://sites.google.com/view/ke-toHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Excited to share PCGrad, a super simple & effective method for multi-task learning & multi-task RL: project conflicting gradients On Meta-World MT50, PCGrad can solve *2x* more tasks than prior methods https://arxiv.org/abs/2001.06782 w/ Tianhe Yu, S Kumar, Gupta,
@svlevine,@hausman_kpic.twitter.com/uTeUhULUTA
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Check out this awesome project that BAIR student Greg Kahn (http://people.eecs.berkeley.edu/~gregoryk/ ) worked on at
@SkydioHQ on training an autonomous deep neural network pilot to film while avoiding obstacles!https://twitter.com/SkydioHQ/status/1217181284922875904 …
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Can suboptimal trials serve as optimal demos? Suboptimal trials are "optimal" for a policy that *aims* to be suboptimal. By conditioning policy on the reward (or advantage) we want it to get, we can use all trials as demos: https://arxiv.org/abs/1912.13465 w/ Aviral Kumar &
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Can robots learn about the world by observing humans? Learn to predict with both interaction & observation (of humans), then use the model to accomplish goals. http://arxiv.org/abs/1912.12773 http://sites.google.com/view/lpmfoai w. Schmeckpeper
@GRASPlab, Xie,@_oleh, Tian,@KostasPenn,@svlevinepic.twitter.com/2EeW02Dmy8Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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It’s time to get rid of
#gpu / tpu / cuda dependencies. On premises training with a new end-to-end#MachineLearning framework is a solution if the#AI dev put efforts on it. While#tensorflow is production ready and#pytorch is a choice for#research they both miss flexibility.https://twitter.com/_brohrer_/status/1210549761612402695 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Video & slides for LIRE workshop @
#NeurIPS2019 are now up: https://sites.google.com/view/neurips2019lire/schedule … Check out the Talks and Panel by@RaiaHadsell@tommmitchell Jeff Bilmes@pabbeel@YejinChoinka Tom Griffiths & more. Thanks to all speakers & presenters for making the workshop a success!pic.twitter.com/2WvsHpEkyZ
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A new
#AI tasked with opening pill bottles, designed by@UCLA scientists, could also explain its actions in multiple ways while it performed the task. Learn more about this study, funded by@DARPA's explainable AI program: https://fcld.ly/zdo33ax pic.twitter.com/hSGYEkJgXEHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Can we discover structure & meta-learn across it in unsegmented time series data? MOCA simultaneously detects changepoints & meta-learns across time for continuous adaptation Continuous Meta-Learning without Tasks https://arxiv.org/abs/1912.08866 w
@jmes_harrison, Sharma,@MarcoPavoneSUpic.twitter.com/fDMCd9MumVHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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This is what recognition datasets should be (if they have any value at all)... easy for humans, hard for machines!https://twitter.com/_abarbu_/status/1204855464720134144 …
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