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Found 6 papers, 1 papers with code
DeGCN: Deformable Graph Convolutional Networks for Skeleton-Based Action Recognition
Graph convolutional networks (GCN) have recently been studied to exploit the graph topology of the human body for skeleton-based action recognition.
Ranked #1 on
Skeleton Based Action Recognition
on NTU RGB+D 120
Tighter 'Uniform Bounds for Black-Scholes Implied Volatility' and the applications to root-finding
This note improves the lower and upper bounds of the Black-Scholes implied volatility (IV) in Tehranchi (SIAM J.
Precognition in Task-oriented Dialogue Understanding: Posterior Regularization by Future Context
And only historical information is used for inference.
UJNLP at SemEval-2020 Task 12: Detecting Offensive Language Using Bidirectional Transformers
In this paper, we built several pre-trained models to participate SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media.
An equation-of-state-meter of quantum chromodynamics transition from deep learning
A primordial state of matter consisting of free quarks and gluons that existed in the early universe a few microseconds after the Big Bang is also expected to form in high-energy heavy-ion collisions.
An equation-of-state-meter of QCD transition from deep learning
Supervised learning with a deep convolutional neural network is used to identify the QCD equation of state (EoS) employed in relativistic hydrodynamic simulations of heavy-ion collisions from the simulated final-state particle spectra $\rho(p_T,\Phi)$.
