activity
20182022
most citedBayesian differential programming for robust systems identification under uncertainty

8 citations · 29 across the 6 of their papers we have counts for

collaborators

17 papers

cs.LG20221 cited

Towards Theoretically Inspired Neural Initialization Optimization

Yibo Yang, Hong Wang, Haobo Yuan +1

Automated machine learning has been widely explored to reduce human efforts in designing neural architectures and looking for proper hyperparameters. In the domain of neural initia…

cs.CV20218 cited

Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search

Yibo Yang, Shan You, Hongyang Li +3

Most differentiable neural architecture search methods construct a super-net for search and derive a target-net as its sub-graph for evaluation. There exists a significant gap betw…

cs.CV2020

ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding

Yibo Yang, Hongyang Li, Shan You +3

Neural architecture search (NAS) aims to produce the optimal sparse solution from a high-dimensional space spanned by all candidate connections. Current gradient-based NAS methods…

eess.IV2020

Improving Inference for Neural Image Compression

Yibo Yang, Robert Bamler, Stephan Mandt

We consider the problem of lossy image compression with deep latent variable models. State-of-the-art methods build on hierarchical variational autoencoders (VAEs) and learn infere…

cs.LG20208 cited

Bayesian differential programming for robust systems identification under uncertainty

Yibo Yang, Mohamed Aziz Bhouri, Paris Perdikaris

This paper presents a machine learning framework for Bayesian systems identification from noisy, sparse and irregular observations of nonlinear dynamical systems. The proposed meth…

cs.CV2020

Spatial Pyramid Based Graph Reasoning for Semantic Segmentation

Xia Li, Yibo Yang, Qijie Zhao +3

The convolution operation suffers from a limited receptive filed, while global modeling is fundamental to dense prediction tasks, such as semantic segmentation. In this paper, we a…