The presently accelerating universe may keep accelerating forever, eventually run into the event horizon problem, and thus be in conflict with the superstring idea. In the other way around, the current accelerating phase as well as the fate of the universe may be swayed by a negative cosmological constant, which dictates a big crunch. Based on the current observational data, in this paper we in...

We present a simple method for assessing the quality of generated images in Generative Adversarial Networks (GANs). The method can be applied in any kind of GAN without interfering with the learning procedure or affecting the learning objective. The central idea is to define a likelihood function that correlates with the quality of the generated images. In particular, we derive a Gaussian likel...

Semi-supervised learning methods based on generative adversarial networks (GANs) obtained strong empirical results, but it is not clear 1) how the discriminator benefits from joint training with a generator, and 2) why good semi-supervised classification performance and a good generator cannot be obtained at the same time. Theoretically we show that given the discriminator objective, good semis...

We propose a method for semi-supervised training of structured-output neural networks. Inspired by the framework of Generative Adversarial Networks (GAN), we train a discriminator network to capture the notion of a ‘quality’ of network output. To this end, we leverage the qualitative difference between outputs obtained on the labelled training data and unannotated data. We then use the discrimi...

The temporal resolution of a 40 mm diameter chevron microchannel plate (MCP) detector followed by a constant fraction discriminator and a time-to-digital converter was determined by using the third order harmonic of 25 fs Ti:sapphire laser pulses. The resolution was found to deteriorate from 200 to 300 ps as the total voltage applied on the two MCPs increased from 1600 to 2000 V. This was likel...

This paper presents noncoherent limiter-discriminator detection and differential detection of FQPSK (Feher quadrature phase-shift-keying) with maximum-likelihood sequence estimation (MLSE) techniques. Noncoherent FQPSK systems are suitable for fast fading and cochannel interference channels and channels with strong phase noise, and they can offer faster synchronization and reduce outage events ...

We introduce a simple semi-supervised learning approach for images based on in-painting using an adversarial loss. Images with random patches removed are presented to a generator whose task is to fill in the hole, based on the surrounding pixels. The in-painted images are then presented to a discriminator network that judges if they are real (unaltered training images) or not. This task acts as...

We propose two experimental schemes for quantum state discrimination that achieve the optimal tradeoff between the probability of correct identification and the disturbance on the quantum state.