Playing hard exploration games by watching YouTube"

Paper by DeepMind: https://papers.nips.cc/paper/7557-playing-hard-exploration-games-by-watching-youtube.pdf

Video: https://www.youtube.com/watch?v=s8ZSVfYmtpc&feature=youtu.be



#AI #AIFirst #ArtificialIntelligence #MontrealAI #NeurIPS #NeurIPS2018

NeurIPS 2018

Videos: https://nips.cc/Conferences/2018/Videos

#artificialintelligence #deeplearning #machinelearning #NeurIPS #NeurIPS2018

Summaries of Top AI Research Papers of 2018

https://www.topbots.com/most-important-ai-research-papers-2018/

#NeurIPS #NeurIPS2018 #NIPS #NIPS2018

"Behind the Selection of the NeurIPS 2019 Workshops"

By Neural Information Processing Systems Conference: https://medium.com/@NeurIPSConf/2019workshops-ec820e4d558e

#MachineLearning #Neurips2019 #DeepLearning #ReinforcementLearning #Neurips

Behind the Selection of the NeurIPS 2019 Workshops"

By Neural Information Processing Systems Conference: https://medium.com/@NeurIPSConf/2019workshops-ec820e4d558e

#MachineLearning #Neurips2019 #DeepLearning #ReinforcementLearning #Neurips

NeurIPS | 2019

Thirty-third Conference on Neural Information Processing Systems - Accepted Competitions :https://neurips.cc/Conferences/2019/CallForCompetitions

#DeepLearning #NeurIPS #NeurIPS2019

NeurIPS 2019 : Disentanglement Challenge
Blog by Max Planck Institute for Intelligent Systems: https://www.aicrowd.com/challenges/neurips-2019-disentanglement-challenge
#DeepLearning #Disentanglement #NeurIPS #NeurIPS2019

Carnegie Mellon University, Accepted Papers at NeurIPS 2019

Learn more → https://mld.ai/neurips2019

#NeurIPS2019 #NeurIPS #MachineLearning #ML #ComputationalNeuroscience #Research #CarnegieMellon #CMUAI #mldcmu

NeurIPS 2019 Stats
Blog by Diego Charrez : https://medium.com/@dcharrezt/neurips-2019-stats-c91346d31c8f
#MachineLearning #Neurips #Neurips2019 #ArtficialIntelligence

Announcing NeurIPS Meetups!
By Neural Information Processing Systems Conference : https://medium.com/@NeurIPSConf/announcing-neurips-meetups-44b2385c67a2
#NeurIPS #Meetup #NeurIPS2019

We just released our #NeurIPS2019 Multimodal Model-Agnostic Meta-Learning (MMAML) code for learning few-shot image classification, which extends MAML to multimodal task distributions (e.g. learning from multiple datasets). The code contains #PyTorch implementations of our model and two baselines (MAML and Multi-MAML) as well as the scripts to evaluate these models to five popular few-shot learning datasets: Omniglot, Mini-ImageNet, FC100 (CIFAR100), CUB-200-2011, and FGVC-Aircraft.

Code: https://github.com/shaohua0116/MMAML-Classification

Paper: https://arxiv.org/abs/1910.13616

#NeurIPS #MachineLearning #ML #code

You have a paper accepted at #NeurIPS but will not be in Vancouver? Consider presenting your work at a local meetup →

https://www.google.com/maps/d/u/0/viewer?mid=1ezbjW7AGg_9APIshVTu09uhJbXkMO5SI&ll=17.28121049467974%2C13.983942200000001&z=-1&fbclid=IwAR2nvS6YA1SnvCetrI8noxOH5ZSPLjwydMxS2vbhlqd9OBQCpFY1krS5t0A