Foraging Under Uncertainty Follows the Marginal Value Theorem with Bayesian Updating of Environment Representations

Kavli Affiliate: Daeyeol Lee | Authors: James Webb, Paul Steffan, Benjamin Y Hayden, Daeyeol Lee, Caleb Kemere and Matthew McGinley | Summary: Foraging theory has been a remarkably successful approach to understanding the behavior of animals in many contexts. In patch-based foraging contexts, the marginal value theorem (MVT) shows that the optimal strategy is to […]


Continue.. Foraging Under Uncertainty Follows the Marginal Value Theorem with Bayesian Updating of Environment Representations

A new approach for deducing rms proton radii from charge-changing reactions of neutron-rich nuclei and the reaction-target dependence

Kavli Affiliate: Feng Wang | First 5 Authors: J. -C. Zhang, B. -H. Sun, I. Tanihata, R. Kanungo, C. Scheidenberger | Summary: We report the charge-changing cross sections ($sigma_{text{cc}}$) of 24 $p$-shell nuclides on both hydrogen and carbon at about 900$A$ MeV, of which $^{8,9}$Li, $^{10textendash12}$Be, $^{10,14,15}$B, $^{14,15,17textendash22}$N and $^{16}$O on hydrogen and $^{8,9}$Li on […]


Continue.. A new approach for deducing rms proton radii from charge-changing reactions of neutron-rich nuclei and the reaction-target dependence

Learning enhances behaviorally relevant representations in apical dendrites

Kavli Affiliate: Elizabeth Hillman | Authors: Sam E. Benezra, Kripa B. Patel, Citlali Pérez Campos, Elizabeth M. C. Hillman and Randy M Bruno | Summary: Learning alters cortical representations and improves perception. Apical tuft dendrites in Layer 1, which are unique in their connectivity and biophysical properties, may be a key site of learning-induced plasticity. […]


Continue.. Learning enhances behaviorally relevant representations in apical dendrites

HSIMamba: Hyperpsectral Imaging Efficient Feature Learning with Bidirectional State Space for Classification

Kavli Affiliate: Jing Wang | First 5 Authors: Judy X Yang, Jun Zhou, Jing Wang, Hui Tian, Alan Wee Chung Liew | Summary: Classifying hyperspectral images is a difficult task in remote sensing, due to their complex high-dimensional data. To address this challenge, we propose HSIMamba, a novel framework that uses bidirectional reversed convolutional neural […]


Continue.. HSIMamba: Hyperpsectral Imaging Efficient Feature Learning with Bidirectional State Space for Classification

Partially-Observable Sequential Change-Point Detection for Autocorrelated Data via Upper Confidence Region

Kavli Affiliate: Xian Chen | First 5 Authors: Haijie Xu, Xiaochen Xian, Chen Zhang, Kaibo Liu, | Summary: Sequential change point detection for multivariate autocorrelated data is a very common problem in practice. However, when the sensing resources are limited, only a subset of variables from the multivariate system can be observed at each sensing […]


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Contributions of mirror-image hair cell orientation to mouse otolith organ and zebrafish neuromast function

Kavli Affiliate: Kathleen Cullen | Authors: Kazuya Ono, Amandine Jarysta, Natasha Hughes, Alma Jukic, Vanessa H.H. Chang, Michael R Deans, Ruth Anne Eatock, Kathleen E Cullen, Katie S Kindt and Basile Tarchini | Summary: Otolith organs in the inner ear and neuromasts in the fish lateral-line harbor two populations of hair cells oriented to detect […]


Continue.. Contributions of mirror-image hair cell orientation to mouse otolith organ and zebrafish neuromast function

Semantically-Shifted Incremental Adapter-Tuning is A Continual ViTransformer

Kavli Affiliate: Ke Wang | First 5 Authors: Yuwen Tan, Qinhao Zhou, Xiang Xiang, Ke Wang, Yuchuan Wu | Summary: Class-incremental learning (CIL) aims to enable models to continuously learn new classes while overcoming catastrophic forgetting. The introduction of pre-trained models has brought new tuning paradigms to CIL. In this paper, we revisit different parameter-efficient […]


Continue.. Semantically-Shifted Incremental Adapter-Tuning is A Continual ViTransformer

Enhancing the General Agent Capabilities of Low-Parameter LLMs through Tuning and Multi-Branch Reasoning

Kavli Affiliate: Ke Wang | First 5 Authors: Qinhao Zhou, Zihan Zhang, Xiang Xiang, Ke Wang, Yuchuan Wu | Summary: Open-source pre-trained Large Language Models (LLMs) exhibit strong language understanding and generation capabilities, making them highly successful in a variety of tasks. However, when used as agents for dealing with complex problems in the real […]


Continue.. Enhancing the General Agent Capabilities of Low-Parameter LLMs through Tuning and Multi-Branch Reasoning

Bioenergetic mapping of ‘healthy microbiomes’ via compound processing potential imprinted in gut and soil metagenomes

Kavli Affiliate: Robert Edwards | Authors: Craig Liddicoat, Robert A Edwards, Michael J. Roach, Jake M Robinson, Kiri Joy Wallace, Andrew D Barnes, Joel Brame, Anna Heintz-Buschart, Timothy R Cavagnaro, Elizabeth A Dinsdale, Michael P Doane, Nico Eisenhauer, Grace Mitchell, Bibishan Rai, Sunita Ramesh and Martin F Breed | Summary: Microbiomes are critical to the […]


Continue.. Bioenergetic mapping of ‘healthy microbiomes’ via compound processing potential imprinted in gut and soil metagenomes

Three-dimensional assessments are necessary to determine the true, spatially-resolved composition of tissues

Kavli Affiliate: Denis Wirtz | Authors: André Forjaz, Eduarda Vaz, Valentina Matos Romero, Saurabh Joshi, Alicia M. Braxton, Ann C. Jiang, Kohei Fujikura, Toby Cornish, Seung-Mo Hong, Ralph H. Hruban, Pei-Hsun Wu, Laura D. Wood, Ashley L. Kiemen and Denis Wirtz | Summary: Methods for spatially resolved cellular profiling using thinly cut sections have enabled […]


Continue.. Three-dimensional assessments are necessary to determine the true, spatially-resolved composition of tissues