normalizing flow
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
In the policy evaluation steps, the critic is updated to capture the soft Q-function. In the policy improvement steps, the actor is adjusted in accordance with the updated soft Q-function.
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- Research Report > New Finding (1.00)
- Research Report > Experimental Study (1.00)
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- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.45)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Maximum Entropy (0.41)
Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows
Achieving a balance between image quality (precision) and diversity (recall) is a significant challenge in the domain of generative models.
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- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
- Information Technology > Artificial Intelligence > Natural Language (0.68)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.67)
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- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Europe > Germany (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.69)
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- North America > United States > Minnesota > Hennepin County > Minneapolis (0.14)
- Asia > Middle East > Jordan (0.05)
- Europe > Sweden > Stockholm > Stockholm (0.04)
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- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.68)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.46)
FlowPG: Action-constrained Policy Gradient with Normalizing Flows
Second, learning the flow model requires sampling from the feasible action space, which is also challenging.
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
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- Europe > Netherlands > North Holland > Amsterdam (0.04)
- Europe > Denmark (0.04)
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- Europe > France > Hauts-de-France > Nord > Lille (0.04)
- Oceania > Australia > New South Wales > Sydney (0.04)
- North America > United States > California > San Diego County > San Diego (0.04)
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.64)
Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference
We take advantage of NF preconditioning and NF based Metropolis-Hastings updates for a faster convergence.
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- Asia > Middle East > Jordan (0.04)
- North America > United States > California > Los Angeles County > Long Beach (0.04)
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