Zobrazeno 1 - 10
of 95
pro vyhledávání: '"Joshi, Sarang P"'
Image registration is a core task in computational anatomy that establishes correspondences between images. Invertible deformable registration, which computes a deformation field and handles complex, non-linear transformation, is essential for tracki
Externí odkaz:
http://arxiv.org/abs/2412.16129
Autor:
Viszlai, Joshua, Chadwick, Jason D., Joshi, Sarang, Ravi, Gokul Subramanian, Li, Yanjing, Chong, Frederic T.
Real-time decoding is a key ingredient in future fault-tolerant quantum systems, yet many decoders are too slow to run in real time. Prior work has shown that parallel window decoding schemes can scalably meet throughput requirements in the presence
Externí odkaz:
http://arxiv.org/abs/2412.05115
Autor:
Dai, Haocheng, Joshi, Sarang
Large vision-language models (VLMs), such as CLIP, have become foundational, demonstrating remarkable success across a variety of downstream tasks. Despite their advantages, these models, akin to other foundational systems, inherit biases from the di
Externí odkaz:
http://arxiv.org/abs/2405.14030
The variational autoencoder (VAE) is a well-studied, deep, latent-variable model (DLVM) that efficiently optimizes the variational lower bound of the log marginal data likelihood and has a strong theoretical foundation. However, the VAE's known failu
Externí odkaz:
http://arxiv.org/abs/2311.07693
Homography estimation is a basic image-alignment method in many applications. Recently, with the development of convolutional neural networks (CNNs), some learning based approaches have shown great success in this task. However, the performance acros
Externí odkaz:
http://arxiv.org/abs/2304.09976
Neural operator learning as a means of mapping between complex function spaces has garnered significant attention in the field of computational science and engineering (CS&E). In this paper, we apply Neural operator learning to the time-of-flight ult
Externí odkaz:
http://arxiv.org/abs/2304.03297
The goal of diffusion-weighted magnetic resonance imaging (DWI) is to infer the structural connectivity of an individual subject's brain in vivo. To statistically study the variability and differences between normal and abnormal brain connectomes, a
Externí odkaz:
http://arxiv.org/abs/2203.06122
We present schemes for simulating Brownian bridges on complete and connected Lie groups and homogeneous spaces. We use this to construct an estimation scheme for recovering an unknown left- or right-invariant Riemannian metric on the Lie group from s
Externí odkaz:
http://arxiv.org/abs/2112.00866
Autor:
Campbell, Kristen M., Dai, Haocheng, Su, Zhe, Bauer, Martin, Fletcher, P. Thomas, Joshi, Sarang C.
The structural network of the brain, or structural connectome, can be represented by fiber bundles generated by a variety of tractography methods. While such methods give qualitative insights into brain structure, there is controversy over whether th
Externí odkaz:
http://arxiv.org/abs/2109.09808
Autor:
Foote, Markus D., Dennison, Philip E., Sullivan, Patrick R., O'Neill, Kelly B., Thorpe, Andrew K., Thompson, David R., Cusworth, Daniel H., Duren, Riley, Joshi, Sarang C.
Publikováno v:
Remote Sensing of Environment, Volume 264, October 2021, 112574
Matched filter (MF) techniques have been widely used for retrieval of greenhouse gas enhancements (enh.) from imaging spectroscopy datasets. While multiple algorithmic techniques and refinements have been proposed, the greenhouse gas target spectrum
Externí odkaz:
http://arxiv.org/abs/2107.05578