Zobrazeno 1 - 10
of 5 992
pro vyhledávání: '"MURPHY, KEVIN"'
Autor:
Murphy, Kevin Robert
Surface tension is an essential force for the functioning of the world and life. Centuries of study, and still, new applications and limits of surface tension are being explored. Water has always drawn attention for its high surface tension value, 72
Externí odkaz:
http://hdl.handle.net/10919/111938
Autor:
Gururaja, Sireesh, Zhang, Yueheng, Tang, Guannan, Zhang, Tianhao, Murphy, Kevin, Yi, Yu-Tsen, Seo, Junwon, Rollett, Anthony, Strubell, Emma
Recent years in NLP have seen the continued development of domain-specific information extraction tools for scientific documents, alongside the release of increasingly multimodal pretrained transformer models. While the opportunity for scientists out
Externí odkaz:
http://arxiv.org/abs/2410.23478
Autor:
Zhou, Guangyao, Swaminathan, Sivaramakrishnan, Raju, Rajkumar Vasudeva, Guntupalli, J. Swaroop, Lehrach, Wolfgang, Ortiz, Joseph, Dedieu, Antoine, Lázaro-Gredilla, Miguel, Murphy, Kevin
We propose Diffusion Model Predictive Control (D-MPC), a novel MPC approach that learns a multi-step action proposal and a multi-step dynamics model, both using diffusion models, and combines them for use in online MPC. On the popular D4RL benchmark,
Externí odkaz:
http://arxiv.org/abs/2410.05364
Autor:
Ortiz, Joseph, Dedieu, Antoine, Lehrach, Wolfgang, Guntupalli, Swaroop, Wendelken, Carter, Humayun, Ahmad, Zhou, Guangyao, Swaminathan, Sivaramakrishnan, Lázaro-Gredilla, Miguel, Murphy, Kevin
Learning from previously collected data via behavioral cloning or offline reinforcement learning (RL) is a powerful recipe for scaling generalist agents by avoiding the need for expensive online learning. Despite strong generalization in some respect
Externí odkaz:
http://arxiv.org/abs/2409.18330
Autor:
Yan, Su, Vié, Clotilde, Lerendegui, Marcelo, Verinaz-Jadan, Herman, Yan, Jipeng, Tashkova, Martina, Burn, James, Wang, Bingxue, Frost, Gary, Murphy, Kevin G., Tang, Meng-Xing
Super-resolution ultrasound imaging through microbubble (MB) localisation and tracking, also known as ultrasound localisation microscopy, allows non-invasive sub-diffraction resolution imaging of microvasculature in animals and humans. The number of
Externí odkaz:
http://arxiv.org/abs/2407.06373
We propose an approach to simulating trajectories of multiple interacting agents (road users) based on transformers and probabilistic graphical models (PGMs), and apply it to the Waymo SimAgents challenge. The transformer baseline is based on the MTR
Externí odkaz:
http://arxiv.org/abs/2406.19635
Multiple types of inference are available for probabilistic graphical models, e.g., marginal, maximum-a-posteriori, and even marginal maximum-a-posteriori. Which one do researchers mean when they talk about "planning as inference"? There is no consis
Externí odkaz:
http://arxiv.org/abs/2406.17863
Publikováno v:
NeurIPS 2024
We propose a novel approach to sequential Bayesian inference based on variational Bayes (VB). The key insight is that, in the online setting, we do not need to add the KL term to regularize to the prior (which comes from the posterior at the previous
Externí odkaz:
http://arxiv.org/abs/2405.19681
Autor:
Xie, Sirui, Xiao, Zhisheng, Kingma, Diederik P, Hou, Tingbo, Wu, Ying Nian, Murphy, Kevin Patrick, Salimans, Tim, Poole, Ben, Gao, Ruiqi
While diffusion models can learn complex distributions, sampling requires a computationally expensive iterative process. Existing distillation methods enable efficient sampling, but have notable limitations, such as performance degradation with very
Externí odkaz:
http://arxiv.org/abs/2405.16852
Autor:
Duran-Martin, Gerardo, Altamirano, Matias, Shestopaloff, Alexander Y., Sánchez-Betancourt, Leandro, Knoblauch, Jeremias, Jones, Matt, Briol, François-Xavier, Murphy, Kevin
We derive a novel, provably robust, and closed-form Bayesian update rule for online filtering in state-space models in the presence of outliers and misspecified measurement models. Our method combines generalised Bayesian inference with filtering met
Externí odkaz:
http://arxiv.org/abs/2405.05646