How Does Our Visual System Achieve Shift and Size Invariance?

The question of shift and size invariance in the primate visual system is discussed. After a short review of the relevant neurobiology and psychophysics, a more detailed analysis of computational models is given. The two main types of networks considered are the dynamic routing circuit model and invariant feature networks, such as the neocognitron. Some specific open questions in context of these models are raised and possible solutions discussed

Learning Generative Models with Visual Attention

Attention has long been proposed by psychologists as important for effectively dealing with the enormous sensory stimulus available in the neocortex. Inspired by the visual attention models in computational neuroscience and the need of object-centric data for generative models, we describe for generative learning framework using attentional mechanisms. Attentional mechanisms can propagate signals from region of interest in a scene to an aligned canonical representation, where generative modeling takes place. By ignoring background clutter, generative models can concentrate their resources on the object of interest. Our model is a proper graphical model where the 2D Similarity transformation is a part of the top-down process. A ConvNet is employed to provide good initializations during posterior inference which is based on Hamiltonian Monte Carlo. Upon learning images of faces, our model can robustly attend to face regions of novel test subjects. More importantly, our model can learn generative models of new faces from a novel dataset of large images where the face locations are not known.Comment: In the proceedings of Neural Information Processing Systems, 201

Reflectionless Sharp Bends and Corners in Waveguides Using Epsilon-Near-Zero Effects

Following our recent theoretical and experimental results that show how zero-permittivity metamaterials may provide anomalous tunneling and energy squeezing through ultranarrow waveguide channels, here we report an experimental investigation of the bending features relative to this counterintuitive resonant effect. We generate the required effectively-zero permittivity using a waveguide operating at the cut-off of its dominant mode, and we show how sharp and narrow bends may be inserted within the propagation channel without causing any sensible reflection or loss.Comment: 13 pages, 6 figure

High-performance 3D waveguide architecture for astronomical pupil-remapping interferometry

The detection and characterisation of extra-solar planets is a major theme driving modern astronomy, with the vast majority of such measurements being achieved by Doppler radial-velocity and transit observations. Another technique -- direct imaging -- can access a parameter space that complements these methods, and paves the way for future technologies capable of detailed characterization of exoplanetary atmospheres and surfaces. However achieving the required levels of performance with direct imaging, particularly from ground-based telescopes which must contend with the Earth's turbulent atmosphere, requires considerable sophistication in the instrument and detection strategy. Here we demonstrate a new generation of photonic pupil-remapping devices which build upon the interferometric framework developed for the {\it Dragonfly} instrument: a high contrast waveguide-based device which recovers robust complex visibility observables. New generation Dragonfly devices overcome problems caused by interference from unguided light and low throughput, promising unprecedented on-sky performance. Closure phase measurement scatter of only $\sim 0.2^\circ$ has been achieved, with waveguide throughputs of $> 70\%$. This translates to a maximum contrast-ratio sensitivity (between the host star and its orbiting planet) at $1 \lambda/D$ (1$\sigma$ detection) of $5.3 \times 10^{-4}$ (when a conventional adaptive-optics (AO) system is used) or $1.8 \times 10^{-4}$ (for typical `extreme-AO' performance), improving even further when random error is minimised by averaging over multiple exposures. This is an order of magnitude beyond conventional pupil-segmenting interferometry techniques (such as aperture masking), allowing a previously inaccessible part of the star to planet contrast-separation parameter space to be explored

Modeling Tiered Pricing in the Internet Transit Market

ISPs are increasingly selling "tiered" contracts, which offer Internet connectivity to wholesale customers in bundles, at rates based on the cost of the links that the traffic in the bundle is traversing. Although providers have already begun to implement and deploy tiered pricing contracts, little is known about how such pricing affects ISPs and their customers. While contracts that sell connectivity on finer granularities improve market efficiency, they are also more costly for ISPs to implement and more difficult for customers to understand. In this work we present two contributions: (1) we develop a novel way of mapping traffic and topology data to a demand and cost model; and (2) we fit this model on three large real-world networks: an European transit ISP, a content distribution network, and an academic research network, and run counterfactuals to evaluate the effects of different pricing strategies on both the ISP profit and the consumer surplus. We highlight three core findings. First, ISPs gain most of the profits with only three or four pricing tiers and likely have little incentive to increase granularity of pricing even further. Second, we show that consumer surplus follows closely, if not precisely, the increases in ISP profit with more pricing tiers. Finally, the common ISP practice of structuring tiered contracts according to the cost of carrying the traffic flows (e.g., offering a discount for traffic that is local) can be suboptimal and that dividing contracts based on both traffic demand and the cost of carrying it into only three or four tiers yields near-optimal profit for the ISP