The THESAN project: connecting ionized bubble sizes to their local environments during the Epoch of Reionization

Posted by dbos MIT

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Meredith Neyer, Aaron Smith, Rahul Kannan, Mark Vogelsberger, Enrico Garaldi | Summary: An important characteristic of cosmic hydrogen reionization is the growth of ionized gas bubbles surrounding early luminous objects. Ionized bubble sizes are beginning to be probed using Lyman-$alpha$ emission from high-redshift galaxies, and will also […]


Continue.. The THESAN project: connecting ionized bubble sizes to their local environments during the Epoch of Reionization

Axion Universal Gravitational Wave Interpretation of Pulsar Timing Array Data

Posted by dbos Tokyo

Kavli Affiliate: Misao Sasaki | First 5 Authors: Kaloian D. Lozanov, Shi Pi, Misao Sasaki, Volodymyr Takhistov, Ao Wang | Summary: Formation of cosmological solitons is generically accompanied by production of gravitational waves (GWs), with a universal GW background expected at frequency scales below that of non-linear dynamics. Beginning with a general phenomenological description of […]


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SimLOD: Simultaneous LOD Generation and Rendering

Posted by dbos Delft

Kavli Affiliate: Michael Wimmer | First 5 Authors: Markus Schütz, Lukas Herzberger, Michael Wimmer, , | Summary: About: We propose an incremental LOD generation approach for point clouds that allows us to simultaneously load points from disk, update an octree-based level-of-detail representation, and render the intermediate results in real time while additional points are still […]


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Certifiably Robust Graph Contrastive Learning

Posted by klaurent Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang | Summary: Graph Contrastive Learning (GCL) has emerged as a popular unsupervised graph representation learning method. However, it has been shown that GCL is vulnerable to adversarial attacks on both the graph structure and node attributes. Although […]


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Whole-cortex in situ sequencing reveals peripheral input-dependent cell type-defined area identity

Posted by dbos Hopkins

Kavli Affiliate: Patrick Kanold | Authors: Xiaoyin Chen, Stephan Fischer, Mara CP Rue, Aixin Zhang, Didhiti Mukherjee, Patrick O Kanold, Jesse Gillis and Anthony Zador | Summary: The cortex is composed of neuronal types with diverse gene expression that are organized into specialized cortical areas. These areas, each with characteristic cytoarchitecture (Brodmann 1909; Vogt and […]


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Retrosplenial inputs drive diverse visual representations in the medial entorhinal cortex

Posted by dbos Yale

Kavli Affiliate: Michael J Higley | Authors: Olivier Dubanet and Michael J. Higley | Summary: The ability of rodents to use visual cues for successful navigation and goal-directed behavior has been long appreciated, although the neural mechanisms supporting sensory representations in navigational circuits are largely unknown. Navigation is fundamentally dependent on the hippocampus and closely […]


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Optimization and Evaluation of Multi Robot Surface Inspection Through Particle Swarm Optimization

Posted by dbos Harvard

Kavli Affiliate: Radhika Nagpal | First 5 Authors: Darren Chiu, Radhika Nagpal, Bahar Haghighat, , | Summary: Robot swarms can be tasked with a variety of automated sensing and inspection applications in aerial, aquatic, and surface environments. In this paper, we study a simplified two-outcome surface inspection task. We task a group of robots to […]


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Dual Prompt Tuning for Domain-Aware Federated Learning

Posted by klaurent Berkeley

Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain […]


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Dual Prompt Tuning for Domain-Aware Federated Learning

Posted by dbos Berkeley

Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain […]


Continue.. Dual Prompt Tuning for Domain-Aware Federated Learning

Dual Prompt Tuning for Domain-Aware Federated Learning

Posted by dbos Berkeley

Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain […]


Continue.. Dual Prompt Tuning for Domain-Aware Federated Learning