Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Hao Zhu"'
Publikováno v:
AAAI
Understanding and modeling behavior of multi-agent systems is a central step for artificial intelligence. Here we present a deep generative model which captures behavior generating process of multi-agent systems, supports accurate predictions and inf
Publikováno v:
Ecotoxicol Environ Saf
Read-across has become a primary approach to fill data gaps for chemical safety assessments. Chemical similarity based on structure, reactivity, and physic-chemical property information is a traditional approach applied for read-across toxicity studi
Publikováno v:
ICPR
We propose a new task named Audio-driven Performance Video Generation (APVG), which aims to synthesize the video of a person playing a certain instrument guided by a given music audio clip. It is a challenging task to generate the high-dimensional te
Publikováno v:
ICPR
Given a speech clip and facial image, the goal of talking face generation is to synthesize a talking face video with accurate mouth synchronization and natural face motion. Recent progress has proven the effectiveness of the landmarks as the intermed
Autor:
Hao Zhu, Yifei Zhang
Publikováno v:
ICASSP
Learning to hash via generative models has became a promising paradigm for fast similarity search in document retrieval. The binary hash codes are treated as Bernoulli latent variables when training a variational autoencoder (VAE). However, the prior
Publikováno v:
Ecotoxicol Environ Saf
Health risks induced by PM(2.5) have become one of the major concerns among living populations, especially in regions facing serious pollution such as China and India. Furthermore, the composition of PM(2.5) is complex and it also varies with time an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dcefbf70513777c3782bb41281e7fe2d
https://europepmc.org/articles/PMC7018436/
https://europepmc.org/articles/PMC7018436/
Publikováno v:
Scopus-Elsevier
EMNLP/IJCNLP (1)
EMNLP/IJCNLP (1)
We present FewRel 2.0, a more challenging task to investigate two aspects of few-shot relation classification models: (1) Can they adapt to a new domain with only a handful of instances? (2) Can they detect none-of-the-above (NOTA) relations? To cons
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fbc0747e00d0315e3e833d491f78ae79
http://arxiv.org/abs/1910.07124
http://arxiv.org/abs/1910.07124
Autor:
Heather L. Ciallella, Hao Zhu
Publikováno v:
Chemical research in toxicology. 32(4)
In 2016, the Frank R. Lautenberg Chemical Safety for the 21st Century Act became the first US legislation to advance chemical safety evaluations by utilizing novel testing approaches that reduce the testing of vertebrate animals. Central to this miss
Autor:
Hao Zhu, Yifei Zhang
Publikováno v:
NAACL-HLT (1)
Learning to hash via generative model has become a powerful paradigm for fast similarity search in documents retrieval. To get binary representation (i.e., hash codes), the discrete distribution prior (i.e., Bernoulli Distribution) is applied to trai
Publikováno v:
NAACL-HLT (1)
We introduce neural finite state transducers (NFSTs), a family of string transduction models defining joint and conditional probability distributions over pairs of strings. The probability of a string pair is obtained by marginalizing over all its ac