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pro vyhledávání: '"Crooks, P A"'
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GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's trained end-to-end across text, vision, and audio, meaning all inputs
Externí odkaz:
http://arxiv.org/abs/2410.21276
Autor:
Aifer, Maxwell, Duffield, Samuel, Donatella, Kaelan, Melanson, Denis, Klett, Phoebe, Belateche, Zach, Crooks, Gavin, Martinez, Antonio J., Coles, Patrick J.
A fully Bayesian treatment of complicated predictive models (such as deep neural networks) would enable rigorous uncertainty quantification and the automation of higher-level tasks including model selection. However, the intractability of sampling Ba
Externí odkaz:
http://arxiv.org/abs/2410.01793
Autor:
Amiri, Hossein, Kohn, Will, Ruan, Shiyang, Kim, Joon-Seok, Kavak, Hamdi, Crooks, Andrew, Pfoser, Dieter, Wenk, Carola, Zufle, Andreas
We demonstrate the Patterns of Life Simulation to create realistic simulations of human mobility in a city. This simulation has recently been used to generate massive amounts of trajectory and check-in data. Our demonstration focuses on using the sim
Externí odkaz:
http://arxiv.org/abs/2410.00185
Autor:
Crooks, Peter, Mayrand, Maxence
We use shifted symplectic geometry to construct the Moore-Tachikawa topological quantum field theories (TQFTs) in a category of Hamiltonian schemes. Our new and overarching insight is an algebraic explanation for the existence of these TQFTs, i.e. th
Externí odkaz:
http://arxiv.org/abs/2409.03532
Today's mainstream network timing models for distributed computing are synchrony, partial synchrony, and asynchrony. These models are coarse-grained and often make either too strong or too weak assumptions about the network. This paper introduces a n
Externí odkaz:
http://arxiv.org/abs/2408.12853
Autor:
Crooks, Peter, Mayrand, Maxence
We develop an affine scheme-theoretic version of Hamiltonian reduction by symplectic groupoids. It works over $\Bbbk=\mathbb{R}$ or $\Bbbk=\mathbb{C}$, and is formulated for an affine symplectic groupoid $\mathcal{G}\rightrightarrows X$, an affine Ha
Externí odkaz:
http://arxiv.org/abs/2408.11932
The Confidential Consortium Framework (CCF) is an open-source platform for developing trustworthy and reliable cloud applications. CCF powers Microsoft's Azure Confidential Ledger service and as such it is vital to build confidence in the correctness
Externí odkaz:
http://arxiv.org/abs/2406.17455
Autor:
Donatella, Kaelan, Duffield, Samuel, Aifer, Maxwell, Melanson, Denis, Crooks, Gavin, Coles, Patrick J.
Second-order training methods have better convergence properties than gradient descent but are rarely used in practice for large-scale training due to their computational overhead. This can be viewed as a hardware limitation (imposed by digital compu
Externí odkaz:
http://arxiv.org/abs/2405.13817
Autor:
Aifer, Maxwell, Melanson, Denis, Donatella, Kaelan, Crooks, Gavin, Ahle, Thomas, Coles, Patrick J.
While physics-based computing can offer speed and energy efficiency compared to digital computing, it also is subject to errors that must be mitigated. For example, many error mitigation methods have been proposed for quantum computing. However this
Externí odkaz:
http://arxiv.org/abs/2401.16231
Today's practical, high performance Byzantine Fault Tolerant (BFT) consensus protocols operate in the partial synchrony model. However, existing protocols are inefficient when deployments are indeed partially synchronous. They deliver either low late
Externí odkaz:
http://arxiv.org/abs/2401.10369