Zobrazeno 1 - 10
of 782
pro vyhledávání: '"van Breugel, P."'
Autor:
Boyacıoğlu, Burak, van Breugel, Floris
Given a set of measurements, observability characterizes the distinguishability of a system's initial state, whereas constructability focuses on the final state in a trajectory. In the presence of process and/or measurement noise, the Fisher informat
Externí odkaz:
http://arxiv.org/abs/2410.19975
Tabular data is one of the most ubiquitous modalities, yet the literature on tabular generative foundation models is lagging far behind its text and vision counterparts. Creating such a model is hard, due to the heterogeneous feature spaces of differ
Externí odkaz:
http://arxiv.org/abs/2406.17673
Recent text and image foundation models are incredibly impressive, and these models are attracting an ever-increasing portion of research resources. In this position piece we aim to shift the ML research community's priorities ever so slightly to a d
Externí odkaz:
http://arxiv.org/abs/2405.01147
Autor:
Pérez-García, Fernando, Bond-Taylor, Sam, Sanchez, Pedro P., van Breugel, Boris, Castro, Daniel C., Sharma, Harshita, Salvatelli, Valentina, Wetscherek, Maria T. A., Richardson, Hannah, Lungren, Matthew P., Nori, Aditya, Alvarez-Valle, Javier, Oktay, Ozan, Ilse, Maximilian
Biomedical imaging datasets are often small and biased, meaning that real-world performance of predictive models can be substantially lower than expected from internal testing. This work proposes using generative image editing to simulate dataset shi
Externí odkaz:
http://arxiv.org/abs/2312.12865
Machine Learning (ML) in low-data settings remains an underappreciated yet crucial problem. Hence, data augmentation methods to increase the sample size of datasets needed for ML are key to unlocking the transformative potential of ML in data-deprive
Externí odkaz:
http://arxiv.org/abs/2312.12112
Evaluating the performance of machine learning models on diverse and underrepresented subgroups is essential for ensuring fairness and reliability in real-world applications. However, accurately assessing model performance becomes challenging due to
Externí odkaz:
http://arxiv.org/abs/2310.16524
Because diffusion models have shown impressive performances in a number of tasks, such as image synthesis, there is a trend in recent works to prove (with certain assumptions) that these models have strong approximation capabilities. In this paper, w
Externí odkaz:
http://arxiv.org/abs/2309.14068
Autor:
van Breugel, Boris
The aim of this essay is to better understand the Grasshopper Problem on the surface of the unit sphere. The problem is motivated by analysing Bell inequalities, but can be formulated as a geometric puzzle as follows. Given a white sphere and a bucke
Externí odkaz:
http://arxiv.org/abs/2307.05359
Generating synthetic data through generative models is gaining interest in the ML community and beyond, promising a future where datasets can be tailored to individual needs. Unfortunately, synthetic data is usually not perfect, resulting in potentia
Externí odkaz:
http://arxiv.org/abs/2305.09235
A dynamical system is observable if there is a one-to-one mapping from the system's measured outputs and inputs to all of the system's states. Analytical and empirical tools exist for quantifying the (full state) observability of linear and nonlinear
Externí odkaz:
http://arxiv.org/abs/2304.14313