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of 126
pro vyhledávání: '"Dinneen, Michael P."'
Computer Vision (CV) labelling algorithms play a pivotal role in the domain of low-level vision. For decades, it has been known that these problems can be elegantly formulated as discrete energy minimization problems derived from probabilistic graphi
Externí odkaz:
http://arxiv.org/abs/2312.12848
Autor:
Trejo, José Manuel Agüero, Calude, Cristian S., Dinneen, Michael J., Fedorov, Arkady, Kulikov, Anatoly, Navarathna, Rohit, Svozil, Karl
Publikováno v:
Theoretical Computer Science 1003, 114632 (2024)
A physical system is determined by a finite set of initial conditions and "laws" represented by equations. The system is computable if we can solve the equations in all instances using a "finite body of mathematical knowledge". In this case, if the l
Externí odkaz:
http://arxiv.org/abs/2311.00908
Phylogenetic (evolutionary) trees and networks are leaf-labeled graphs that are widely used to represent the evolutionary relationships between entities such as species, languages, cancer cells, and viruses. To reconstruct and analyze phylogenetic ne
Externí odkaz:
http://arxiv.org/abs/2202.11234
Autor:
Summers, Cecilia, Dinneen, Michael J.
Nondeterminism in neural network optimization produces uncertainty in performance, making small improvements difficult to discern from run-to-run variability. While uncertainty can be reduced by training multiple model copies, doing so is time-consum
Externí odkaz:
http://arxiv.org/abs/2103.04514
Akademický článek
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Autor:
Summers, Cecilia, Dinneen, Michael J.
While great progress has been made at making neural networks effective across a wide range of visual tasks, most models are surprisingly vulnerable. This frailness takes the form of small, carefully chosen perturbations of their input, known as adver
Externí odkaz:
http://arxiv.org/abs/1906.03749
Autor:
Summers, Cecilia, Dinneen, Michael J.
A key component of most neural network architectures is the use of normalization layers, such as Batch Normalization. Despite its common use and large utility in optimizing deep architectures, it has been challenging both to generically improve upon
Externí odkaz:
http://arxiv.org/abs/1906.03548
Akademický článek
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Publikováno v:
EPTCS 273, 2018, pp. 1-13
Quantum annealing has shown significant potential as an approach to near-term quantum computing. Despite promising progress towards obtaining a quantum speedup, quantum annealers are limited by the need to embed problem instances within the (often hi
Externí odkaz:
http://arxiv.org/abs/1807.11135
Publikováno v:
Phys. Scr. 94, 045103 (2019)
The advantages of quantum random number generators (QRNGs) over pseudo-random number generators (PRNGs) are normally attributed to the nature of quantum measurements. This is often seen as implying the superiority of the sequences of bits themselves
Externí odkaz:
http://arxiv.org/abs/1806.08762