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

Posted by klaurent MIT

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Meredith Neyer, Aaron Smith, Rahul Kannan, Mark Vogelsberger, Enrico Garaldi | Summary: An important characteristic of cosmic reionization is the growth of ionized gas bubbles surrounding early luminous objects. Understanding the connections between the formation and coalescence of these bubbles and their originating astrophysical sources is equally […]


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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Learning to Prompt Your Domain for Vision-Language Models

Posted by dbos Berkeley

Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Prompt learning has recently become a very efficient transfer learning paradigm for Contrastive Language Image Pretraining (CLIP) models. Compared with fine-tuning the entire encoder, prompt learning can obtain highly competitive results by optimizing only a small number […]


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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 […]


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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