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pro vyhledávání: '"Foo, A"'
Resistance to therapy remains a significant challenge in cancer treatment, often due to the presence of a stem-like cell population that drives tumor recurrence post-treatment. Moreover, many anticancer drugs inadvertently induce plasticity, revertin
Externí odkaz:
http://arxiv.org/abs/2409.18879
Autor:
Kim, Kanghyun, Chaware, Amey, Cook, Clare B., Xu, Shiqi, Abdelmalak, Monica, Cooke, Colin, Zhou, Kevin C., Harfouche, Mark, Reamey, Paul, Saliu, Veton, Doman, Jed, Dugo, Clay, Horstmeyer, Gregor, Davis, Richard, Taylor-Cho, Ian, Foo, Wen-Chi, Kreiss, Lucas, Jiang, Xiaoyin Sara, Horstmeyer, Roarke
Optical microscopy has long been the standard method for diagnosis in cytopathology. Whole slide scanners can image and digitize large sample areas automatically, but are slow, expensive and therefore not widely available. Clinical diagnosis of cytol
Externí odkaz:
http://arxiv.org/abs/2409.15722
Magnetic superconductors manifest a fascinating interplay between their magnetic and superconducting properties. This becomes evident, for example, in the significant enhancement of the upper critical field observed in uranium-based superconductors,
Externí odkaz:
http://arxiv.org/abs/2409.12494
Language based editing of 3D human avatars to precisely match user requirements is challenging due to the inherent ambiguity and limited expressiveness of natural language. To overcome this, we propose the Avatar Concept Slider (ACS), a 3D avatar edi
Externí odkaz:
http://arxiv.org/abs/2408.13995
Autor:
Foo, Cheng, Hamilton, Eleanor
Accurate waveform modelling is crucial for parameter estimation in gravitational wave astronomy, impacting our understanding of source properties and the testing of general relativity. The precession of orbital and spin angular momenta in binary blac
Externí odkaz:
http://arxiv.org/abs/2408.02671
Machine unlearning (MU) seeks to remove knowledge of specific data samples from trained models without the necessity for complete retraining, a task made challenging by the dual objectives of effective erasure of data and maintaining the overall perf
Externí odkaz:
http://arxiv.org/abs/2407.10494
Autor:
Lau, Gregory Kang Ruey, Niu, Xinyuan, Dao, Hieu, Chen, Jiangwei, Foo, Chuan-Sheng, Low, Bryan Kian Hsiang
Protecting intellectual property (IP) of text such as articles and code is increasingly important, especially as sophisticated attacks become possible, such as paraphrasing by large language models (LLMs) or even unauthorized training of LLMs on copy
Externí odkaz:
http://arxiv.org/abs/2407.04411
We propose an experimental setup to probe the interplay between the quantum superposition principle and the gravitational time dilation arising from the mass-energy equivalence. It capitalizes on state-of-the-art atom interferometers that can keep at
Externí odkaz:
http://arxiv.org/abs/2406.19037
Autor:
Foo, Jessica, Khoo, Shaun
As large language models (LLMs) become increasingly prevalent in a wide variety of applications, concerns about the safety of their outputs have become more significant. Most efforts at safety-tuning or moderation today take on a predominantly Wester
Externí odkaz:
http://arxiv.org/abs/2407.10995
Autor:
Dasgupta, Agnimitra, Ramaswamy, Harisankar, Murgoitio-Esandi, Javier, Foo, Ken, Li, Runze, Zhou, Qifa, Kennedy, Brendan, Oberai, Assad
We propose a framework to perform Bayesian inference using conditional score-based diffusion models to solve a class of inverse problems in mechanics involving the inference of a specimen's spatially varying material properties from noisy measurement
Externí odkaz:
http://arxiv.org/abs/2406.13154