Composable Text Controls in Latent Space with ODEs

Kavli Affiliate: Feng Yuan | First 5 Authors: Guangyi Liu, Zeyu Feng, Yuan Gao, Zichao Yang, Xiaodan Liang | Summary: Real-world text applications often involve composing a wide range of text control operations, such as editing the text w.r.t. an attribute, manipulating keywords and structure, and generating new text of desired properties. Prior work typically […]


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Newly discovered $zsim5$ quasars based on deep learning and Bayesian information criterion

Kavli Affiliate: Linhua Jiang | First 5 Authors: Suhyun Shin, Myungshin Im, Yongjung Kim, Linhua Jiang, | Summary: We report the discovery of four quasars with $M_{1450} gtrsim -25.0$ mag at $zsim5$ and supermassive black hole mass measurement for one of the quasars. They were selected as promising high-redshift quasar candidates via deep learning and […]


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Conserved charges in the quantum simulation of integrable spin chains

Kavli Affiliate: Masahito Yamazaki | First 5 Authors: Kazunobu Maruyoshi, Takuya Okuda, Juan William Pedersen, Ryo Suzuki, Masahito Yamazaki | Summary: When simulating the time evolution of quantum many-body systems on a digital quantum computer, one faces the challenges of quantum noise and of the Trotter error due to time discretization. The Trotter error in […]


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Estimating Cosmological Constraints from Galaxy Cluster Abundance using Simulation-Based Inference

Kavli Affiliate: Brian Nord | First 5 Authors: Moonzarin Reza, Yuanyuan Zhang, Brian Nord, Jason Poh, Aleksandra Ciprijanovic | Summary: Inferring the values and uncertainties of cosmological parameters in a cosmology model is of paramount importance for modern cosmic observations. In this paper, we use the simulation-based inference (SBI) approach to estimate cosmological constraints from […]


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Testing the key role of the stellar mass-halo mass relation in galaxy merger rates and morphologies via DECODE, a novel Discrete statistical sEmi-empiriCal mODEl

| First 5 authors: [#feed_custom_author[1]], [#feed_custom_author[2]], [#feed_custom_author[3]], [#feed_custom_author[4]], [#feed_custom_author[5]] | Summary: The relative roles of mergers and star formation in regulating galaxy growth are still a matter of intense debate. We here present our DECODE, a new Discrete statistical sEmi-empiriCal mODEl specifically designed to predict rapidly and efficiently, in a full cosmological context, galaxy assembly […]


Continue.. Testing the key role of the stellar mass-halo mass relation in galaxy merger rates and morphologies via DECODE, a novel Discrete statistical sEmi-empiriCal mODEl

Improved Polarization Calibration of the BICEP3 CMB Polarimeter at the South Pole

Kavli Affiliate: Chao-Lin Kuo | First 5 Authors: J. Cornelison, C. Vergès, P. A. R. Ade, Z. Ahmed, M. Amiri | Summary: The BICEP3 Polarimeter is a small aperture, refracting telescope, dedicated to the observation of the Cosmic Microwave Background (CMB) at 95GHz. It is designed to target degree angular scale polarization patterns, in particular […]


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AlphaVC: High-Performance and Efficient Learned Video Compression

Kavli Affiliate: Jing Wang | First 5 Authors: Yibo Shi, Yunying Ge, Jing Wang, Jue Mao, | Summary: Recently, learned video compression has drawn lots of attention and show a rapid development trend with promising results. However, the previous works still suffer from some criticial issues and have a performance gap with traditional compression standards […]


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Polarizations of Gravitational Waves in the Bumblebee Gravity Model

Kavli Affiliate: Lijing Shao | First 5 Authors: Dicong Liang, Rui Xu, Xuchen Lu, Lijing Shao, | Summary: Lorentz violation modifies the dispersion relation of gravitational waves (GWs), and induces birefringence and anisotropy in propagation. Our study shows that Lorentz violation can also activate multiple polarizations of GWs. We use the gauge invariants to investigate […]


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Content-oriented learned image compression

Kavli Affiliate: Jing Wang | First 5 Authors: Meng Li, Shangyin Gao, Yihui Feng, Yibo Shi, Jing Wang | Summary: In recent years, with the development of deep neural networks, end-to-end optimized image compression has made significant progress and exceeded the classic methods in terms of rate-distortion performance. However, most learning-based image compression methods are […]


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