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- Policy Smoothing Description: Policy smoothing is a technique used in the field of reinforcement learning that aims to make an agent's policy less sensitive to(...) Read more
- Policy Evaluation Metrics Description: Policy evaluation metrics in the context of reinforcement learning are quantitative measures that allow for the analysis and(...) Read more
- Policy Robustness Description: Policy robustness in the context of reinforcement learning refers to the ability of a policy to maintain effective and consistent(...) Read more
- Policy Exploration Description: Policy exploration in the context of reinforcement learning refers to the process of testing different strategies or policies to(...) Read more
- Policy Dynamics Description: Policy dynamics in the context of reinforcement learning refer to the evolution of policies and decisions as an agent interacts(...) Read more
- Progressive Growing GAN Description: The 'Progressive Growing GAN' is a type of Generative Adversarial Network characterized by its innovative approach to training(...) Read more
- PatchGAN Description: PatchGAN is a Generative Adversarial Network (GAN) architecture that focuses on classifying image patches rather than evaluating(...) Read more
- Parameter sharing Description: Parameter sharing is a technique used in the field of large language models (LLMs) that involves using the same parameters across(...) Read more
- Pre-trained model Description: A pre-trained model is a type of machine learning model that has been previously trained on a massive dataset before being(...) Read more
- Pixel normalization Description: Pixel normalization is the process of adjusting pixel values to a common scale, allowing images to be more consistent and(...) Read more
- Projection Discriminator Description: The Projection Discriminator is a key component in Generative Adversarial Networks (GANs), designed to evaluate the authenticity of(...) Read more
- Pyramid Pooling Description: Pyramid pooling is a technique that uses multiple pooling layers at different scales to capture spatial information. This(...) Read more
- Perceptual Similarity Description: Perceptual similarity is a measure that evaluates how similar two images appear to a human observer. This concept is fundamental in(...) Read more
- PixelCNN Description: PixelCNN is a generative model that uses convolutional neural networks to model the pixel distribution in images. Unlike other(...) Read more
- Pseudorandom Noise Description: Pseudorandom noise is a type of noise generated by deterministic algorithms that simulate randomness. Unlike truly random noise,(...) Read more
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