Learning Fused State Representations for Control from Multi-View Observations

Kavli Affiliate: Li Xin Li | First 5 Authors: Zeyu Wang, Yao-Hui Li, Xin Li, Hongyu Zang, Romain Laroche | Summary: Multi-View Reinforcement Learning (MVRL) seeks to provide agents with multi-view observations, enabling them to perceive environment with greater effectiveness and precision. Recent advancements in MVRL focus on extracting latent representations from multiview observations and […]


Continue.. Learning Fused State Representations for Control from Multi-View Observations

Learning Fused State Representations for Control from Multi-View Observations

Kavli Affiliate: Li Xin Li | First 5 Authors: Zeyu Wang, Yao-Hui Li, Xin Li, Hongyu Zang, Romain Laroche | Summary: Multi-View Reinforcement Learning (MVRL) seeks to provide agents with multi-view observations, enabling them to perceive environment with greater effectiveness and precision. Recent advancements in MVRL focus on extracting latent representations from multiview observations and […]


Continue.. Learning Fused State Representations for Control from Multi-View Observations

A practical Bayesian method for gravitational-wave ringdown analysis with multiple modes

Kavli Affiliate: Lijing Shao | First 5 Authors: Yiming Dong, Ziming Wang, Hai-Tian Wang, Junjie Zhao, Lijing Shao | Summary: Gravitational-wave (GW) ringdown signals from black holes (BHs) encode crucial information about the gravitational dynamics in the strong-field regime, which offers unique insights into BH properties. In the future, the improving sensitivity of GW detectors […]


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Harnessing the Evolution of Proteostasis Networks to Reverse Cognitive Dysfunction

Kavli Affiliate: Yifan Cheng | Authors: Junrui Li, Yifei chen, Shawn Zheng, Angus McDonald, John W. Sedat, David A. Agard and Yifan Cheng | Summary: With technological advancements in recent years, single particle cryogenic electron microscopy (cryo-EM) has become a major methodology for structural biology. Structure determination by single particle cryo-EM is premised on randomly […]


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Population Representation of the Confidence in a Decision in the Parietal Cortex

Kavli Affiliate: Michael Shadlen | Authors: Ariel Zylberberg and Michael N Shadlen | Summary: Confidence in a decision is the belief, prior to feedback, that one’s choice is correct. In the brain, many decisions are implemented as a race between competing evidence-accumulation processes. We ask whether the neurons that represent evidence accumulation also carry information […]


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Language Models Use Trigonometry to Do Addition

Kavli Affiliate: Max Tegmark | First 5 Authors: Subhash Kantamneni, Max Tegmark, , , | Summary: Mathematical reasoning is an increasingly important indicator of large language model (LLM) capabilities, yet we lack understanding of how LLMs process even simple mathematical tasks. To address this, we reverse engineer how three mid-sized LLMs compute addition. We first […]


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Psychometric-Based Evaluation for Theorem Proving with Large Language Models

Kavli Affiliate: Long Zhang | First 5 Authors: Jianyu Zhang, Yongwang Zhao, Long Zhang, Jilin Hu, Xiaokun Luan | Summary: Large language models (LLMs) for formal theorem proving have become a prominent research focus. At present, the proving ability of these LLMs is mainly evaluated through proof pass rates on datasets such as miniF2F. However, […]


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Cosmological super-resolution of the 21-cm signal

Kavli Affiliate: George Efstathiou | First 5 Authors: Simon Pochinda, Jiten Dhandha, Anastasia Fialkov, Eloy de Lera Acedo, | Summary: In this study, we train score-based diffusion models to super-resolve gigaparsec-scale cosmological simulations of the 21-cm signal. We examine the impact of network and training dataset size on model performance, demonstrating that a single simulation […]


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LEAD: Large Foundation Model for EEG-Based Alzheimer’s Disease Detection

Kavli Affiliate: Xiang Zhang | First 5 Authors: Yihe Wang, Nan Huang, Nadia Mammone, Marco Cecchi, Xiang Zhang | Summary: Electroencephalogram (EEG) provides a non-invasive, highly accessible, and cost-effective solution for Alzheimer’s Disease (AD) detection. However, existing methods, whether based on manual feature extraction or deep learning, face two major challenges: the lack of large-scale […]


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Evaluation of sequencing reads at scale using rdeval

Kavli Affiliate: Erich Jarvis | Authors: Giulio Formenti, Bonhwang Koo, Marco Sollitto, Jennifer Balacco, Nadolina Brajuka, Richard Burhans, Erick Duarte, Alice Maria Giani, Kirsty McCaffrey, Jack A Medico, Eugene W Myers and Erich D Jarvis | Summary: Motivation Large sequencing data sets are produced and deposited into public archives at unprecedented rates. The availability of […]


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