Beyond deep reinforcement learning: A tutorial on generative diffusion models in network optimization
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a …
Generative Artificial Intelligence (GAI), demonstrating their versatility and efficacy across a …
Opportunities and challenges of diffusion models for generative AI
Diffusion models, a powerful and universal generative AI technology, have achieved
tremendous success and opened up new possibilities in diverse applications. In these …
tremendous success and opened up new possibilities in diverse applications. In these …
Noise contrastive alignment of language models with explicit rewards
User intentions are typically formalized as evaluation rewards to be maximized when fine-
tuning language models (LMs). Existing alignment methods, such as Direct Preference …
tuning language models (LMs). Existing alignment methods, such as Direct Preference …
Simple hierarchical planning with diffusion
Diffusion-based generative methods have proven effective in modeling trajectories with
offline datasets. However, they often face computational challenges and can falter in …
offline datasets. However, they often face computational challenges and can falter in …
Consistency models as a rich and efficient policy class for reinforcement learning
Score-based generative models like the diffusion model have been testified to be effective in
modeling multi-modal data from image generation to reinforcement learning (RL). However …
modeling multi-modal data from image generation to reinforcement learning (RL). However …
Safe offline reinforcement learning with feasibility-guided diffusion model
Safe offline RL is a promising way to bypass risky online interactions towards safe policy
learning. Most existing methods only enforce soft constraints, ie, constraining safety …
learning. Most existing methods only enforce soft constraints, ie, constraining safety …
Boosting continuous control with consistency policy
Due to its training stability and strong expression, the diffusion model has attracted
considerable attention in offline reinforcement learning. However, several challenges have …
considerable attention in offline reinforcement learning. However, several challenges have …
Tfg: Unified training-free guidance for diffusion models
Given an unconditional diffusion model and a predictor for a target property of interest (eg, a
classifier), the goal of training-free guidance is to generate samples with desirable target …
classifier), the goal of training-free guidance is to generate samples with desirable target …
Score regularized policy optimization through diffusion behavior
Recent developments in offline reinforcement learning have uncovered the immense
potential of diffusion modeling, which excels at representing heterogeneous behavior …
potential of diffusion modeling, which excels at representing heterogeneous behavior …
Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across …
Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across …