40 citations · 171 across the 18 of their papers we have counts for
19 papers
A Laplace-inspired Distribution on SO(3) for Probabilistic Rotation Estimation
Yingda Yin, Yang Wang, He Wang +1
Estimating the 3DoF rotation from a single RGB image is an important yet challenging problem. Probabilistic rotation regression has raised more and more attention with the benefit…
Grasping Core Rules of Time Series through Pure Models
Gedi Liu, Yifeng Jiang, Yi Ouyang +2
Time series underwent the transition from statistics to deep learning, as did many other machine learning fields. Although it appears that the accuracy has been increasing as the m…
S-Rocket: Selective Random Convolution Kernels for Time Series Classification
Hojjat Salehinejad, Yang Wang, Yuanhao Yu +2
Random convolution kernel transform (Rocket) is a fast, efficient, and novel approach for time series feature extraction using a large number of independent randomly initialized 1-…
Approximation bounds for norm constrained neural networks with applications to regression and GANs
Yuling Jiao, Yang Wang, Yunfei Yang
This paper studies the approximation capacity of ReLU neural networks with norm constraint on the weights. We prove upper and lower bounds on the approximation error of these netwo…
The global landscape of phase retrieval II: quotient intensity models
Jian-Feng Cai, Meng Huang, Dong Li +1
A fundamental problem in phase retrieval is to reconstruct an unknown signal from a set of magnitude-only measurements. In this work we introduce three novel quotient intensity-bas…
The global landscape of phase retrieval I: perturbed amplitude models
Jian-Feng Cai, Meng Huang, Dong Li +1
A fundamental task in phase retrieval is to recover an unknown signal $\vx\in \Rn$ from a set of magnitude-only measurements $y_i=\abs{\nj{\va_i,\vx}}, \; i=1,\ldots,m$. In this pa…