Zobrazeno 1 - 10
of 1 977
pro vyhledávání: '"P. Kavan"'
The realization of fault-tolerant quantum computers hinges on effective quantum error correction protocols, whose performance significantly relies on the nature of the underlying noise. In this work, we directly study the structure of non-Markovian c
Externí odkaz:
http://arxiv.org/abs/2410.23779
HodgeRank generalizes ranking algorithms, e.g. Google PageRank, to rank alternatives based on real-world (often incomplete) data using graphs and discrete exterior calculus. It analyzes multipartite interactions on high-dimensional networks with a co
Externí odkaz:
http://arxiv.org/abs/2407.20452
We present a new method to bake classical facial animation blendshapes into a fast linear blend skinning representation. Previous work explored skinning decomposition methods that approximate general animated meshes using a dense set of bone transfor
Externí odkaz:
http://arxiv.org/abs/2406.11597
Autor:
Chen, Hsiao-yu, Larionov, Egor, Kavan, Ladislav, Lin, Gene, Roble, Doug, Sorkine-Hornung, Olga, Stuyck, Tuur
Well-fitted clothing is essential for both real and virtual garments to enable self-expression and accurate representation for a large variety of body types. Common practice in the industry is to provide a pre-made selection of distinct garment sizes
Externí odkaz:
http://arxiv.org/abs/2405.19148
Autor:
Dowling, Neil, West, Maxwell T., Southwell, Angus, Nakhl, Azar C., Sevior, Martin, Usman, Muhammad, Modi, Kavan
Despite their ever more widespread deployment throughout society, machine learning algorithms remain critically vulnerable to being spoofed by subtle adversarial tampering with their input data. The prospect of near-term quantum computers being capab
Externí odkaz:
http://arxiv.org/abs/2405.10360
Autor:
Chuck, Caleb, Qi, Carl, Munje, Michael J., Li, Shuozhe, Rudolph, Max, Shi, Chang, Agarwal, Siddhant, Sikchi, Harshit, Peri, Abhinav, Dayal, Sarthak, Kuo, Evan, Mehta, Kavan, Wang, Anthony, Stone, Peter, Zhang, Amy, Niekum, Scott
Reinforcement Learning is a promising tool for learning complex policies even in fast-moving and object-interactive domains where human teleoperation or hard-coded policies might fail. To effectively reflect this challenging category of tasks, we int
Externí odkaz:
http://arxiv.org/abs/2405.03113
Noise on quantum devices is much more complex than it is commonly given credit. Far from usual models of decoherence, nearly all quantum devices are plagued both by a continuum of environments and temporal instabilities. These induce noisy quantum an
Externí odkaz:
http://arxiv.org/abs/2312.08454
Autor:
Leditto, Caesnan M. G., Southwell, Angus, Tonekaboni, Behnam, White, Gregory A. L., Usman, Muhammad, Modi, Kavan
Predicting and analyzing global behaviour of complex systems is challenging due to the intricate nature of their component interactions. Recent work has started modelling complex systems using networks endowed with multiway interactions among nodes,
Externí odkaz:
http://arxiv.org/abs/2312.07672
Autor:
Zhang, Xinfang, Wu, Zhihao, White, Gregory A. L., Xiang, Zhongcheng, Hu, Shun, Peng, Zhihui, Liu, Yong, Zheng, Dongning, Fu, Xiang, Huang, Anqi, Poletti, Dario, Modi, Kavan, Wu, Junjie, Deng, Mingtang, Guo, Chu
The development of fault-tolerant quantum processors relies on the ability to control noise. A particularly insidious form of noise is temporally correlated or non-Markovian noise. By combining randomized benchmarking with supervised machine learning
Externí odkaz:
http://arxiv.org/abs/2312.06062
Publikováno v:
Phys. Rev. X 14, 041018 (2024)
We introduce a class of quantum non-Markovian processes -- dubbed process trees -- that exhibit polynomially decaying temporal correlations and memory distributed across time scales. This class of processes is described by a tensor network with tree-
Externí odkaz:
http://arxiv.org/abs/2312.04624