Zobrazeno 1 - 10
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pro vyhledávání: '"Lawson, Daniel"'
Graph neural networks (GNNs) are powerful black-box models which have shown impressive empirical performance. However, without any form of uncertainty quantification, it can be difficult to trust such models in high-risk scenarios. Conformal predicti
Externí odkaz:
http://arxiv.org/abs/2405.19230
Performing Bayesian inference for the Epidemic-Type Aftershock Sequence (ETAS) model of earthquakes typically requires MCMC sampling using the likelihood function or estimating the latent branching structure. These tasks have computational complexity
Externí odkaz:
http://arxiv.org/abs/2404.16590
In this paper, we address the problem of dynamic network embedding, that is, representing the nodes of a dynamic network as evolving vectors within a low-dimensional space. While the field of static network embedding is wide and established, the fiel
Externí odkaz:
http://arxiv.org/abs/2311.09251
The development of the next generation of optical phase change technologies for integrated photonic and free-space platforms relies on the availability of materials that can be switched repeatedly over large volumes and with low optical losses. In re
Externí odkaz:
http://arxiv.org/abs/2310.10252
Autor:
Lawson, Daniel, Qureshi, Ahmed H.
Recent work has shown the promise of creating generalist, transformer-based, models for language, vision, and sequential decision-making problems. To create such models, we generally require centralized training objectives, data, and compute. It is o
Externí odkaz:
http://arxiv.org/abs/2303.07551
Synthesizing planning and control policies in robotics is a fundamental task, further complicated by factors such as complex logic specifications and high-dimensional robot dynamics. This paper presents a novel reinforcement learning approach to solv
Externí odkaz:
http://arxiv.org/abs/2303.01346
Point processes have been dominant in modeling the evolution of seismicity for decades, with the Epidemic Type Aftershock Sequence (ETAS) model being most popular. Recent advances in machine learning have constructed highly flexible point process mod
Externí odkaz:
http://arxiv.org/abs/2301.09948
Autor:
Lawson, Daniel, Qureshi, Ahmed H.
Learning long-horizon tasks such as navigation has presented difficult challenges for successfully applying reinforcement learning to robotics. From another perspective, under known environments, sampling-based planning can robustly find collision-fr
Externí odkaz:
http://arxiv.org/abs/2211.06407
Autor:
Lawson, Daniel
This dissertation examines the role the medium of comics plays in the construction and subversion of anti-Arab and Islamophobic discourse. It seeks to address the following questions in particular: how does the medium of comics interpellate subjects
Externí odkaz:
http://hdl.handle.net/10919/77058
http://scholar.lib.vt.edu/theses/available/etd-05042011-145743/
http://scholar.lib.vt.edu/theses/available/etd-05042011-145743/
The antimony-based chalcogenide Sb2Se3 is a rapidly emerging material for photonic phase change applications owing to its ultra-low optical losses at telecommunication wavelengths in both crystalline and amorphous phases. Here, we investigate the dyn
Externí odkaz:
http://arxiv.org/abs/2111.13182