Adversarial Variational Embedding for Robust Semi-supervised Learning

Semi-supervised learning is sought for leveraging the unlabelled data when labelled data is difficult or expensive to acquire. Deep generative models (e.g., Variational Autoencoder (VAE)) and semisupervised Generative Adversarial Networks (GANs) have recently shown promising performance in semi-supervised classification for the excellent discriminative representing ability. However, the latent code learned by the traditional VAE is not exclusive (repeatable) for a specific input sample, which prevents it from excellent classification performance. In particular, the learned latent representation depends on a non-exclusive component which is stochastically sampled from the prior distribution. Moreover, the semi-supervised GAN models generate data from pre-defined distribution (e.g., Gaussian noises) which is independent of the input data distribution and may obstruct the convergence and is difficult to control the distribution of the generated data. To address the aforementioned issues, we propose a novel Adversarial Variational Embedding (AVAE) framework for robust and effective semi-supervised learning to leverage both the advantage of GAN as a high quality generative model and VAE as a posterior distribution learner. The proposed approach first produces an exclusive latent code by the model which we call VAE++, and meanwhile, provides a meaningful prior distribution for the generator of GAN. The proposed approach is evaluated over four different real-world applications and we show that our method outperforms the state-of-the-art models, which confirms that the combination of VAE++ and GAN can provide significant improvements in semisupervised classification.Comment: 9 pages, Accepted by Research Track in KDD 201

Observation of subdiffusive dynamic scaling in a driven and disordered box-trapped Bose gas

We explore the dynamics of a tuneable box-trapped Bose gas under strong periodic forcing in the presence of weak disorder. In absence of interparticle interactions, the interplay of the drive and disorder results in an isotropic nonthermal momentum distribution that shows subdiffusive dynamic scaling, with sublinear energy growth and the universal scaling function captured well by a compressed exponential. For increasing interaction strength, the gas behavior crosses over to wave turbulence characterized by a power-law momentum distribution.Comment: Main text (4 pages, 4 figures), Supplemental Material (2 pages, 4 figures

Realizing spin squeezing with Rydberg interactions in a programmable optical clock

Neutral-atom arrays trapped in optical potentials are a powerful platform for studying quantum physics, combining precise single-particle control and detection with a range of tunable entangling interactions. For example, these capabilities have been leveraged for state-of-the-art frequency metrology as well as microscopic studies of entangled many-particle states. In this work, we combine these applications to realize spin squeezing - a widely studied operation for producing metrologically useful entanglement - in an optical atomic clock based on a programmable array of interacting optical qubits. In this first demonstration of Rydberg-mediated squeezing with a neutral-atom optical clock, we generate states that have almost 4 dB of metrological gain. Additionally, we perform a synchronous frequency comparison between independent squeezed states and observe a fractional frequency stability of $1.087(1)\times 10^{-15}$ at one-second averaging time, which is 1.94(1) dB below the standard quantum limit, and reaches a fractional precision at the $10^{-17}$ level during a half-hour measurement. We further leverage the programmable control afforded by optical tweezer arrays to apply local phase shifts in order to explore spin squeezing in measurements that operate beyond the relative coherence time with the optical local oscillator. The realization of this spin-squeezing protocol in a programmable atom-array clock opens the door to a wide range of quantum-information inspired techniques for optimal phase estimation and Heisenberg-limited optical atomic clocks.Comment: 13 pages, 4 figures; Supplementary Informatio

Interaction-driven breakdown of dynamical localization in a kicked quantum gas

Quantum interference can terminate energy growth in a continually kicked system, via a single-particle ergodicity-breaking mechanism known as dynamical localization. The effect of many-body interactions on dynamically localized states, while important to a fundamental understanding of quantum decoherence, has remained unexplored despite a quarter-century of experimental studies. We report the experimental realization of a tunably-interacting kicked quantum rotor ensemble using a Bose-Einstein condensate in a pulsed optical lattice. We observe signatures of a prethermal localized plateau, followed for interacting samples by interaction-induced anomalous diffusion with an exponent near one half. Echo-type time reversal experiments establish the role of interactions in destroying reversibility. These results quantitatively elucidate the dynamical transition to many-body quantum chaos, advance our understanding of quantum anomalous diffusion, and delimit some possibilities for protecting quantum information in interacting driven systems.Comment: 17 pages including supp inf

mTOR signaling in VIP neurons regulates circadian clock synchrony and olfaction

Mammalian/mechanistic target of rapamycin (mTOR) signaling controls cell growth, proliferation, and metabolism in dividing cells. Less is known regarding its function in postmitotic neurons in the adult brain. Here we created a conditional mTOR knockout mouse model to address this question. Using the Cre-LoxP system, the mTOR gene was specifically knocked out in cells expressing Vip (vasoactive intestinal peptide), which represent a major population of interneurons widely distributed in the neocortex, suprachiasmatic nucleus (SCN), olfactory bulb (OB), and other brain regions. Using a combination of biochemical, behavioral, and imaging approaches, we found that mice lacking mTOR in VIP neurons displayed erratic circadian behavior and weakened synchronization among cells in the SCN, the master circadian pacemaker in mammals. Furthermore, we have discovered a critical role for mTOR signaling in mediating olfaction. Odor stimulated mTOR activation in the OB, anterior olfactory nucleus, as well as piriform cortex. Odor-evoked c-Fos responses along the olfactory pathway were abolished in mice lacking mTOR in VIP neurons, which is consistent with reduced olfactory sensitivity in these animals. Together, these results demonstrate that mTOR is a key regulator of SCN circadian clock synchrony and olfaction

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Prophet model for forecasting occupancy presence in indoor spaces using non-intrusive sensors

The Internet of Things is a multi-sensor technology with the unique advantage of supporting non-intrusive and non-device occupancy detection, while also allowing us to explore new forecasting occupancy models. However, forecasting occupancy presence is not a trivial task, since it is still unknown the main criteria in selecting a forecasting modelling approach according to a non-intrusive sensing strategy. Towards this challenge, this paper proposes an analytical workflow developed to support the Prophet model for forecasting occupancy presence in indoor spaces throughout the tasks of sensing, processing, and analysing event triggered data generated from ten non-intrusive sensors, including motion, temperature, luminosity, CO2, TVOC, sound, pressure, accelerometer, gyroscope, and humidity sensors. The usefulness of this analytical workflow is demonstrated with the implementation of an IoT platform for an experiment operating non-intrusive sensing in a classroom. The assessment is made at different time intervals and the results confirm that there is a relationship between the event-count and occupancy presence in such a way that the larger the number of events triggered in an indoor space, the higher the probability of an indoor space being occupied

Observation of subdiffusive dynamic scaling in a driven and disordered Bose gas

We explore the dynamics of a tuneable box-trapped Bose gas under strong periodic forcing in the presence of weak disorder. In absence of interparticle interactions, the interplay of the drive and disorder results in an isotropic nonthermal momentum distribution that shows subdiffusive dynamic scaling, with sublinear energy growth and the universal scaling function captured well by a compressed exponential. We explain that this subdiffusion in momentum space can naturally be understood as a random walk in energy space. We also experimentally show that for increasing interaction strength, the gas behavior smoothly crosses over to wave turbulence characterized by a power-law momentum distribution, which opens new possibilities for systematic studies of the interplay of disorder and interactions in driven quantum systems

Research data supporting "Observation of Subdiffusive Dynamic Scaling in a Driven and Disordered Bose Gas"

The data summary includes the measured momentum distributions, and further processed data, such as atom numbers and energies, obtained using destructive absorption imaging of our samples after time of flight expansion, and averaging over experimental repetitions