Search Results for author:
Found 9 papers, 5 papers with code
HMPC-assisted Adversarial Inverse Reinforcement Learning for Smart Home Energy Management
This letter proposes an Adversarial Inverse Reinforcement Learning (AIRL)-based energy management method for a smart home, which incorporates an implicit thermal dynamics model.
REF-VLM: Triplet-Based Referring Paradigm for Unified Visual Decoding
To address complex visual decoding scenarios, we introduce the Triplet-Based Referring Paradigm (TRP), which explicitly decouples three critical dimensions in visual decoding tasks through a triplet structure: concepts, decoding types, and targets.
An Ordinary Differential Equation Sampler with Stochastic Start for Diffusion Bridge Models
To mitigate this gap, we propose a high-order ODE sampler with a stochastic start for diffusion bridge models.
CaRtGS: Computational Alignment for Real-Time Gaussian Splatting SLAM
To address this, we introduce Computational Alignment for Real-Time Gaussian Splatting SLAM (CaRtGS), a novel method enhancing the efficiency and quality of photorealistic scene reconstruction in real-time environments.
Learning from Pattern Completion: Self-supervised Controllable Generation
Inspired by the neural mechanisms that may contribute to the brain's associative power, specifically the cortical modularization and hippocampal pattern completion, here we propose a self-supervised controllable generation (SCG) framework.
Implicit Image-to-Image Schrodinger Bridge for Image Restoration
The Image-to-Image Schr\"odinger Bridge (I$^2$SB) offers a promising alternative by initializing the generative process from corrupted images while leveraging training techniques from score-based diffusion models.
AI of Brain and Cognitive Sciences: From the Perspective of First Principles
Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation.
S3E: A Multi-Robot Multimodal Dataset for Collaborative SLAM
The burgeoning demand for collaborative robotic systems to execute complex tasks collectively has intensified the research community's focus on advancing simultaneous localization and mapping (SLAM) in a cooperative context.
Unsupervised Learnable Sinogram Inpainting Network (SIN) for Limited Angle CT reconstruction
In this paper, we propose a sinogram inpainting network (SIN) to solve limited-angle CT reconstruction problem, which is a very challenging ill-posed issue and of great interest for several clinical applications.
Medical Physics Image and Video Processing
