9,165 research outputs found
Task-set switching with natural scenes: Measuring the cost of deploying top-down attention
In many everyday situations, we bias our perception from the top down, based on a task or an agenda. Frequently, this entails shifting attention to a specific attribute of a particular object or scene. To explore the cost of shifting top-down attention to a different stimulus attribute, we adopt the task-set switching paradigm, in which switch trials are contrasted with repeat trials in mixed-task blocks and with single-task blocks. Using two tasks that relate to the content of a natural scene in a gray-level photograph and two tasks that relate to the color of the frame around the image, we were able to distinguish switch costs with and without shifts of attention. We found a significant cost in reaction time of 23–31 ms for switches that require shifting attention to other stimulus attributes, but no significant switch cost for switching the task set within an attribute. We conclude that deploying top-down attention to a different attribute incurs a significant cost in reaction time, but that biasing to a different feature value within the same stimulus attribute is effortless
Scene Graph Generation by Iterative Message Passing
Understanding a visual scene goes beyond recognizing individual objects in
isolation. Relationships between objects also constitute rich semantic
information about the scene. In this work, we explicitly model the objects and
their relationships using scene graphs, a visually-grounded graphical structure
of an image. We propose a novel end-to-end model that generates such structured
scene representation from an input image. The model solves the scene graph
inference problem using standard RNNs and learns to iteratively improves its
predictions via message passing. Our joint inference model can take advantage
of contextual cues to make better predictions on objects and their
relationships. The experiments show that our model significantly outperforms
previous methods for generating scene graphs using Visual Genome dataset and
inferring support relations with NYU Depth v2 dataset.Comment: CVPR 201
DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs
A major difficulty of solving continuous POMDPs is to infer the multi-modal
distribution of the unobserved true states and to make the planning algorithm
dependent on the perceived uncertainty. We cast POMDP filtering and planning
problems as two closely related Sequential Monte Carlo (SMC) processes, one
over the real states and the other over the future optimal trajectories, and
combine the merits of these two parts in a new model named the DualSMC network.
In particular, we first introduce an adversarial particle filter that leverages
the adversarial relationship between its internal components. Based on the
filtering results, we then propose a planning algorithm that extends the
previous SMC planning approach [Piche et al., 2018] to continuous POMDPs with
an uncertainty-dependent policy. Crucially, not only can DualSMC handle complex
observations such as image input but also it remains highly interpretable. It
is shown to be effective in three continuous POMDP domains: the floor
positioning domain, the 3D light-dark navigation domain, and a modified Reacher
domain.Comment: IJCAI 202
Fractional exclusion and braid statistics in one dimension: a study via dimensional reduction of Chern-Simons theory
The relation between braid and exclusion statistics is examined in
one-dimensional systems, within the framework of Chern-Simons statistical
transmutation in gauge invariant form with an appropriate dimensional
reduction. If the matter action is anomalous, as for chiral fermions, a
relation between braid and exclusion statistics can be established explicitly
for both mutual and nonmutual cases. However, if it is not anomalous, the
exclusion statistics of emergent low energy excitations is not necessarily
connected to the braid statistics of the physical charged fields of the system.
Finally, we also discuss the bosonization of one-dimensional anyonic systems
through T-duality.Comment: 19 pages, fix typo
Reliable energy level alignment at physisorbed molecule-metal interfaces from density functional theory.
A key quantity for molecule-metal interfaces is the energy level alignment of molecular electronic states with the metallic Fermi level. We develop and apply an efficient theoretical method, based on density functional theory (DFT) that can yield quantitatively accurate energy level alignment information for physisorbed metal-molecule interfaces. The method builds on the "DFT+Σ" approach, grounded in many-body perturbation theory, which introduces an approximate electron self-energy that corrects the level alignment obtained from conventional DFT for missing exchange and correlation effects associated with the gas-phase molecule and substrate polarization. Here, we extend the DFT+Σ approach in two important ways: first, we employ optimally tuned range-separated hybrid functionals to compute the gas-phase term, rather than rely on GW or total energy differences as in prior work; second, we use a nonclassical DFT-determined image-charge plane of the metallic surface to compute the substrate polarization term, rather than the classical DFT-derived image plane used previously. We validate this new approach by a detailed comparison with experimental and theoretical reference data for several prototypical molecule-metal interfaces, where excellent agreement with experiment is achieved: benzene on graphite (0001), and 1,4-benzenediamine, Cu-phthalocyanine, and 3,4,9,10-perylene-tetracarboxylic-dianhydride on Au(111). In particular, we show that the method correctly captures level alignment trends across chemical systems and that it retains its accuracy even for molecules for which conventional DFT suffers from severe self-interaction errors
Concurrent Channel Probing and Data Transmission in Full-duplex MIMO Systems
An essential step for achieving multiplexing gain in MIMO downlink systems is
to collect accurate channel state information (CSI) from the users.
Traditionally, CSIs have to be collected before any data can be transmitted.
Such a sequential scheme incurs a large feedback overhead, which substantially
limits the multiplexing gain especially in a network with a large number of
users. In this paper, we propose a novel approach to mitigate the feedback
overhead by leveraging the recently developed Full-duplex radios. Our approach
is based on the key observation that using Full-duplex radios, when the
base-station (BS) is collecting CSI of one user through the uplink channel, it
can use the downlink channel to simultaneously transmit data to other
(non-interfering) users for which CSIs are already known. By allowing
concurrent channel probing and data transmission, our scheme can potentially
achieve a higher throughput compared to traditional schemes using Half-duplex
radios. The new flexibility introduced by our scheme, however, also leads to
fundamental challenges in achieving throughout optimal scheduling. In this
paper, we make an initial effort to this important problem by considering a
simplified group interference model. We develop a throughput optimal scheduling
policy with complexity , where is the number of users and
is the number of user groups. To further reduce the complexity, we propose a
greedy policy with complexity that not only achieves at least 2/3
of the optimal throughput region, but also outperforms any feasible Half-duplex
solutions. We derive the throughput gain offered by Full-duplex under different
system parameters and show the advantage of our algorithms through numerical
studies.Comment: Technical repor
Lower Bound of Concurrence Based on Positive Maps
We study the concurrence of arbitrary dimensional bipartite quantum systems.
An explicit analytical lower bound of concurrence is obtained, which detects
entanglement for some quantum states better than some well-known separability
criteria, and improves the lower bounds such as from the PPT, realignment
criteria and the Breuer's entanglement witness.Comment: 8 pages, 1 figur
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