Error analysis of tensor-train cross approximation
Tensor train decomposition is widely used in machine learning and quantum physics due to
its concise representation of high-dimensional tensors, overcoming the curse of …
its concise representation of high-dimensional tensors, overcoming the curse of …
tntorch: Tensor network learning with PyTorch
We present tntorch, a tensor learning framework that supports multiple decompositions
(including Candecomp/Parafac, Tucker, and Tensor Train) under a unified interface. With …
(including Candecomp/Parafac, Tucker, and Tensor Train) under a unified interface. With …
Tt-nf: Tensor train neural fields
Learning neural fields has been an active topic in deep learning research, focusing, among
other issues, on finding more compact and easy-to-fit representations. In this paper, we …
other issues, on finding more compact and easy-to-fit representations. In this paper, we …
Probabilistic Shape Completion by Estimating Canonical Factors with Hierarchical VAE
We propose a novel method for 3D shape completion from a partial observation of a point
cloud. Existing methods either operate on a global latent code, which limits the …
cloud. Existing methods either operate on a global latent code, which limits the …
A combined CNN-LSTM and LSTM-QRNN model for prediction of Idiopathic Pulmonary Fibrosis Progression using CT Scans and Clinical Data
HBT Anh, TT Dinh, LT Van… - 2022 RIVF International …, 2022 - ieeexplore.ieee.org
Idiopathic Pulmonary Fibrosis (IPF), which causes scarred tissues and lung function damage
over time, is a serious progressive lung disease. In addition, this chronic disease is …
over time, is a serious progressive lung disease. In addition, this chronic disease is …
Bayesian optimization in the wild: risk-averse and computationally-effective decision-making
A Makarova - 2023 - research-collection.ethz.ch
Sequential decision-making in some complex and uncertain environments can be
formalized as optimizing a black-box function. For example, in drug design, the aim is to …
formalized as optimizing a black-box function. For example, in drug design, the aim is to …