4 citations · 8 across the 7 of their papers we have counts for
7 papers
On Efficient Neural Network Architectures for Image Compression
Yichi Zhang, Zhihao Duan, Fengqing Zhu
Recent advances in learning-based image compression typically come at the cost of high complexity. Designing computationally efficient architectures remains an open challenge. In t…
Theoretical Bound-Guided Hierarchical VAE for Neural Image Codecs
Yichi Zhang, Zhihao Duan, Yuning Huang +1
Recent studies reveal a significant theoretical link between variational autoencoders (VAEs) and rate-distortion theory, notably in utilizing VAEs to estimate the theoretical upper…
UMOEA/D: A Multiobjective Evolutionary Algorithm for Uniform Pareto Objectives based on Decomposition
Xiaoyuan Zhang, Xi Lin, Yichi Zhang +2
Multiobjective optimization (MOO) is prevalent in numerous applications, in which a Pareto front (PF) is constructed to display optima under various preferences. Previous methods c…
Trainable Fixed-Point Quantization for Deep Learning Acceleration on FPGAs
Dingyi Dai, Yichi Zhang, Jiahao Zhang +4
Quantization is a crucial technique for deploying deep learning models on resource-constrained devices, such as embedded FPGAs. Prior efforts mostly focus on quantizing matrix mult…
Reconstructing microstructures from statistical descriptors using neural cellular automata
Paul Seibert, Alexander Raßloff, Yichi Zhang +4
The problem of generating microstructures of complex materials in silico has been approached from various directions including simulation, Markov, deep learning and descriptor-base…
DA-VEGAN: Differentiably Augmenting VAE-GAN for microstructure reconstruction from extremely small data sets
Yichi Zhang, Paul Seibert, Alexandra Otto +3
Microstructure reconstruction is an important and emerging field of research and an essential foundation to improving inverse computational materials engineering (ICME). Much of th…