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Measuring the Algorithmic Efficiency of Neural NetworksToward Trustworthy AI Development: Mechanisms for Supporting Verifiable ClaimsDeep Double Descent: Where Bigger Models and More Data HurtLeveraging Procedural Generation to Benchmark Reinforcement LearningBenchmarking Safe Exploration in Deep Reinforcement LearningRelease Strategies and the Social Impacts of Language ModelsThe Role of Cooperation in Responsible AI DevelopmentSGD on Neural Networks Learns Functions of Increasing ComplexityTransfer of Adversarial Robustness Between Perturbation TypesImplicit Generation and Generalization in Energy-Based ModelsNeural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent AgentsComputational Limitations in Robust Classification and Win-Win ResultsQuantifying Generalization in Reinforcement LearningPlan Online, Learn Offline: Efficient Learning and Exploration via Model-Based ControlSupervising Strong Learners by Amplifying Weak ExpertsFFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative ModelsDomain Randomization and Generative Models for Robotic GraspingLearning Policy Representations in Multiagent SystemsGlow: Generative Flow with Invertible 1x1 ConvolutionsGamePad: A Learning Environment for Theorem ProvingEmergence of Grounded Compositional Language in Multi-Agent PopulationsGotta Learn Fast: A New Benchmark for Generalization in RLVariance Reduction for Policy Gradient with Action-Dependent Factorized BaselinesSim-to-real Transfer of Robotic Control with Dynamics RandomizationSome Considerations on Learning to Explore via Meta-Reinforcement LearningMulti-Goal Reinforcement Learning: Challenging Robotics Environments and Request for ResearchBackpropagation through the Void: Optimizing Control Variates for Black-Box Gradient EstimationThe Malicious Use of Artificial Intelligence: Forecasting, Prevention, and MitigationDeepType: Multilingual Entity Linking by Neural Type System EvolutionLearning Sparse Neural Networks through L0 RegularizationDomain Randomization and Generative Models for Robotic GraspingAsymmetric Actor Critic for Image-Based Robot LearningContinuous Adaptation via Meta-Learning in Nonstationary and Competitive EnvironmentsMulti-Agent Actor-Critic for Mixed Cooperative-Competitive EnvironmentsEquivalence Between Policy Gradients and Soft Q-LearningStochastic Neural Networks for Hierarchical Reinforcement LearningLearning to Generate Reviews and Discovering SentimentDomain Randomization for Transferring Deep Neural Networks from Simulation to the Real WorldEmergence of Grounded Compositional Language in Multi-Agent PopulationsPrediction and Control with Temporal Segment ModelsEvolution Strategies as a Scalable Alternative to Reinforcement LearningPixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications#Exploration: A Study of Count-Based Exploration for Deep Reinforcement LearningOn the Quantitative Analysis of Decoder-Based Generative ModelsA Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based ModelsRL2: Fast Reinforcement Learning via Slow Reinforcement LearningAdversarial Training Methods for Semi-Supervised Text ClassificationSemi-supervised Knowledge Transfer for Deep Learning from Private Training DataTransfer from Simulation to Real World through Learning Deep Inverse Dynamics ModelImproving Variational Inference with Inverse Autoregressive FlowInfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial NetsWeight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural NetworksVIME: Variational Information Maximizing Exploration OpenAI LP. OpenAI works on advancing AI capabilities, safety, and policy. Am Ende ist ein finanzieller Verlust zu verzeichnen. Reinforcement Learning July 9, 2020. OpenAI works on advancing AI capabilities, safety, and policy. 15 Feb 2020 Paper Code Discrete Action On-Policy Learning with Action-Value Critic. Contribute to openai/gpt-3 development by creating an account on GitHub.

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