661 citations · 1.6k across the 30 of their papers we have counts for
8 papers · 1 filter
Stretchable Cells Help DARTS Search Better
Tao Huang, Shan You, Yibo Yang +4
Differentiable neural architecture search (DARTS) has gained much success in discovering flexible and diverse cell types. To reduce the evaluation gap, the supernet is expected to…
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…
Hierarchical Autoregressive Modeling for Neural Video Compression
Ruihan Yang, Yibo Yang, Joseph Marino +1
Recent work by Marino et al. (2020) showed improved performance in sequential density estimation by combining masked autoregressive flows with hierarchical latent variable models.…
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…
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…
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…
Exact artificial boundary conditions of 1D semi-discretized peridynamics
Songsong Ji, Gang Pang, Jiwei Zhang +2
The peridynamic theory reformulates the equations of continuum mechanics in terms of integro-differential equations instead of partial differential equations. It is not trivial to…
Variational Bayesian Quantization
Yibo Yang, Robert Bamler, Stephan Mandt
We propose a novel algorithm for quantizing continuous latent representations in trained models. Our approach applies to deep probabilistic models, such as variational autoencoders…