Learning Continuous 3D Words for Text-to-Image Generation

Kavli Affiliate: Matthew Fisher | First 5 Authors: Ta-Ying Cheng, Matheus Gadelha, Thibault Groueix, Matthew Fisher, Radomir Mech | Summary: Current controls over diffusion models (e.g., through text or ControlNet) for image generation fall short in recognizing abstract, continuous attributes like illumination direction or non-rigid shape change. In this paper, we present an approach for […]


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Delving into Multi-modal Multi-task Foundation Models for Road Scene Understanding: From Learning Paradigm Perspectives

Kavli Affiliate: Yi Zhou | First 5 Authors: Sheng Luo, Wei Chen, Wanxin Tian, Rui Liu, Luanxuan Hou | Summary: Foundation models have indeed made a profound impact on various fields, emerging as pivotal components that significantly shape the capabilities of intelligent systems. In the context of intelligent vehicles, leveraging the power of foundation models […]


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Skyrmions: A review on materials perspective for future electronic devices

Kavli Affiliate: Cheng Peng | First 5 Authors: Vineet Kumar Sharma, Alana Okullo, Jalen Garner, Cheng Peng, Rajan Plumley | Summary: Recent years have witnessed an enormous rise in research interest in magnetic skyrmions owing to their capability to improve over contemporary spintronic devices. An overview of the various magnetic interactions responsible for the formation […]


Continue.. Skyrmions: A review on materials perspective for future electronic devices

Skyrmions: A review on materials perspective for future electronic devices

Kavli Affiliate: Cheng Peng | First 5 Authors: Vineet Kumar Sharma, Alana Okullo, Jalen Garner, Cheng Peng, Rajan Plumley | Summary: Recent years have witnessed an enormous rise in research interest in magnetic skyrmions owing to their capability to improve over contemporary spintronic devices. An overview of the various magnetic interactions responsible for the formation […]


Continue.. Skyrmions: A review on materials perspective for future electronic devices

Skyrmions: A review on materials perspective for future electronic devices

Kavli Affiliate: Cheng Peng | First 5 Authors: Vineet Kumar Sharma, Alana Okullo, Jalen Garner, Cheng Peng, Rajan Plumley | Summary: Recent years have witnessed an enormous rise in research interest in magnetic skyrmions owing to their capability to improve over contemporary spintronic devices. An overview of the various magnetic interactions responsible for the formation […]


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Multiway junction conditions I: booklets and webs

Kavli Affiliate: Cheng Peng | First 5 Authors: Jia-Yin Shen, Cheng Peng, Li-Xin Li, , | Summary: We explore the construction of gluing together an arbitrary number of spacetimes along a common interface that gives a geometric structure we refer to as the booklet geometry. We derive junction conditions across the interface, in both Einstein […]


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Publication bias adjustment in network meta-analysis: an inverse probability weighting approach using clinical trial registries

Kavli Affiliate: Yi Zhou | First 5 Authors: Ao Huang, Yi Zhou, Satoshi Hattori, , | Summary: Network meta-analysis (NMA) is a useful tool to compare multiple interventions simultaneously in a single meta-analysis, it can be very helpful for medical decision making when the study aims to find the best therapy among several active candidates. […]


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Chirality-induced Phonon-Spin Conversion at an Interface

Kavli Affiliate: Mamoru Matsuo | First 5 Authors: Takumi Funato, Mamoru Matsuo, Takeo Kato, , | Summary: We consider spin injection driven by nonequilibrium chiral phonons from a chiral insulator into an adjacent metal. Phonon-spin conversion arises from the coupling of the electron spin with the microrotation associated with chiral phonons. We derive a microscopic […]


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Machine learning for industrial sensing and control: A survey and practical perspective

Kavli Affiliate: Biao Huang | First 5 Authors: Nathan P. Lawrence, Seshu Kumar Damarla, Jong Woo Kim, Aditya Tulsyan, Faraz Amjad | Summary: With the rise of deep learning, there has been renewed interest within the process industries to utilize data on large-scale nonlinear sensing and control problems. We identify key statistical and machine learning […]


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