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Found 4 papers, 3 papers with code
LCM-LoRA: A Universal Stable-Diffusion Acceleration Module
Latent Consistency Models (LCMs) have achieved impressive performance in accelerating text-to-image generative tasks, producing high-quality images with minimal inference steps.
One is More: Diverse Perspectives within a Single Network for Efficient DRL
Deep reinforcement learning has achieved remarkable performance in various domains by leveraging deep neural networks for approximating value functions and policies.
Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference
Inspired by Consistency Models (song et al.), we propose Latent Consistency Models (LCMs), enabling swift inference with minimal steps on any pre-trained LDMs, including Stable Diffusion (rombach et al).
RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
Training deep reinforcement learning (DRL) models usually requires high computation costs.
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