Zobrazeno 1 - 10
of 2 513
pro vyhledávání: '"Turner Richard"'
Autor:
Shysheya, Aliaksandra, Diaconu, Cristiana, Bergamin, Federico, Perdikaris, Paris, Hernández-Lobato, José Miguel, Turner, Richard E., Mathieu, Emile
Modelling partial differential equations (PDEs) is of crucial importance in science and engineering, and it includes tasks ranging from forecasting to inverse problems, such as data assimilation. However, most previous numerical and machine learning
Externí odkaz:
http://arxiv.org/abs/2410.16415
Autor:
Mlodozeniec, Bruno, Eschenhagen, Runa, Bae, Juhan, Immer, Alexander, Krueger, David, Turner, Richard
Diffusion models have led to significant advancements in generative modelling. Yet their widespread adoption poses challenges regarding data attribution and interpretability. In this paper, we aim to help address such challenges in diffusion models b
Externí odkaz:
http://arxiv.org/abs/2410.13850
Many important problems require modelling large-scale spatio-temporal datasets, with one prevalent example being weather forecasting. Recently, transformer-based approaches have shown great promise in a range of weather forecasting problems. However,
Externí odkaz:
http://arxiv.org/abs/2410.06731
Autor:
Reid, Isaac, Dubey, Kumar Avinava, Jain, Deepali, Whitney, Will, Ahmed, Amr, Ainslie, Joshua, Bewley, Alex, Jacob, Mithun, Mehta, Aranyak, Rendleman, David, Schenck, Connor, Turner, Richard E., Wagner, René, Weller, Adrian, Choromanski, Krzysztof
When training transformers on graph-structured data, incorporating information about the underlying topology is crucial for good performance. Topological masking, a type of relative position encoding, achieves this by upweighting or downweighting att
Externí odkaz:
http://arxiv.org/abs/2410.03462
Autor:
Vaughan, Anna, Mateo-Garcia, Gonzalo, Irakulis-Loitxate, Itziar, Watine, Marc, Fernandez-Poblaciones, Pablo, Turner, Richard E., Requeima, James, Gorroño, Javier, Randles, Cynthia, Caltagirone, Manfredi, Cifarelli, Claudio
Mitigating methane emissions is the fastest way to stop global warming in the short-term and buy humanity time to decarbonise. Despite the demonstrated ability of remote sensing instruments to detect methane plumes, no system has been available to ro
Externí odkaz:
http://arxiv.org/abs/2408.04745
Vision language models (VLMs) demonstrate impressive capabilities in visual question answering and image captioning, acting as a crucial link between visual and language models. However, existing open-source VLMs heavily rely on pretrained and frozen
Externí odkaz:
http://arxiv.org/abs/2407.16526
Autor:
O'Reilly, Malgorzata M., Krasnicki, Sebastian, Montgomery, James, Heydar, Mojtaba, Turner, Richard, Van Dam, Pieter, Maree, Peter
We study the Patient Assignment Scheduling (PAS) problem in a random environment that arises in the management of patient flow in the hospital systems, due to the stochastic nature of the arrivals as well as the Length of Stay distribution. We develo
Externí odkaz:
http://arxiv.org/abs/2406.18618
Neural processes (NPs) are a powerful family of meta-learning models that seek to approximate the posterior predictive map of the ground-truth stochastic process from which each dataset in a meta-dataset is sampled. There are many cases in which prac
Externí odkaz:
http://arxiv.org/abs/2406.13493
Equivariant deep learning architectures exploit symmetries in learning problems to improve the sample efficiency of neural-network-based models and their ability to generalise. However, when modelling real-world data, learning problems are often not
Externí odkaz:
http://arxiv.org/abs/2406.13488
Autor:
Ashman, Matthew, Diaconu, Cristiana, Kim, Junhyuck, Sivaraya, Lakee, Markou, Stratis, Requeima, James, Bruinsma, Wessel P., Turner, Richard E.
The effectiveness of neural processes (NPs) in modelling posterior prediction maps -- the mapping from data to posterior predictive distributions -- has significantly improved since their inception. This improvement can be attributed to two principal
Externí odkaz:
http://arxiv.org/abs/2406.12409