Neural Discrete Representation Learning

Learning useful representations without supervision remains a key challenge in machine learning. In this paper, we propose a simple yet powerful generative model that learns such discrete representations. Our model, the Vector Quantised-Variational AutoEncoder (VQ-VAE), differs from VAEs in two key ways: the encoder network outputs discrete, rather than continuous, codes; and the prior is learnt rather than static. In order to learn a discrete latent representation, we incorporate ideas from vector quantisation (VQ). Using the VQ method allows the model to circumvent issues of "posterior collapse" -- where the latents are ignored when they are paired with a powerful autoregressive decoder -- typically observed in the VAE framework. Pairing these representations with an autoregressive prior, the model can generate high quality images, videos, and speech as well as doing high quality speaker conversion and unsupervised learning of phonemes, providing further evidence of the utility of the learnt representations

Common wave behavior for mergers and acquisitions in OECD countries? a unique analysis using new Markov switching panel model approach

This paper investigates whether or not there is co-waved merger and acquisition (M&A) activity in 26 OECD countries. We apply the Markov Switching model to panel data (MSP hereafter), an approach which has not previously been attempted. Two distinct regimes are recognized in emerge from M&A data: the wave merger regime and normal merger regime. Our MSP captures the co-wave pattern of the sample countries and has a much better fit than either the univariate Markov Switching model or the conventional linear panel model.

Trace Anomaly of Proton Mass with Vector Meson Near-Thresholds Photoproduction Data

Trace anomalous contribution to proton mass is particularly important in understanding the QCD mass structure. The value and the scale-dependent of the trace anomalous energy of the strong interaction are still not clear in combination of theories and experiments. In this paper, we explore the near-threshold photoproduction data of $\phi$ and J/$\psi$ to study the quantum anomalous energy in QCD and its scale-dependence. The vector-meson-dominance model and the van der Waals interaction between the vector meson and the proton are used. We find that the quantum anomalous energy to the proton mass is scale-dependent and it can be described as $M_a=0.25\exp(-A/\mu^2)M_N$ with $A=0.101\pm0.029$ GeV$^2$. The empirical result is consistent with the LQCD calculation at $\mu^2=4$ GeV$^2$. Finally, the corresponding evolution equation for trace anomaly part is given by our calculation.Comment: 6 pages, 4 figures, Corrected spelling mistake