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Animal movement encodes information that is meaningfully interpreted by natural counterparts. This is a behavior that roboticists are trying to replicate in artificial systems but that is not well understood even in natural systems. This paper presents a count on the cardinality of a discretized...

Insects and hummingbirds exhibit extraordinary flight capabilities and can simultaneously master seemingly conflicting goals: stable hovering and aggressive maneuvering, unmatched by small scale man-made vehicles. Flapping Wing Micro Air Vehicles (FWMAVs) hold great promise for closing this...

Interactions within complex network components define their operational modes, collective behaviors and global functionality. Understanding the role of these interactions is limited by either sensing methodologies or intentional adversarial efforts that sabotage the network structure. To overcome...

Importance Hospital readmissions are associated with patient harm and expense. Ways to prevent hospital readmissions have focused on identifying patients at greatest risk using prediction scores.

Objective To identify the type of score that best predicts hospital readmissions.

Design, Setting...

Notwithstanding important advances in the context of single-variant pathogenicity identification, novel breakthroughs in discerning the origins of many rare diseases require methods able to identify more complex genetic models. We present here the Variant Combinations Pathogenicity Predictor...

The problem of retrosynthetic planning can be framed as a one-player game, in which the chemist (or a computer program) works backward from a molecular target to simpler starting materials through a series of choices regarding which reactions to perform. This game is challenging as the combinatorial...

Global agriculture production is challenged by increasing demands from rising population and a changing climate, which may be alleviated through development of genetically improved crop cultivars. Research into increasing photosynthetic energy conversion efficiency has proposed many strategies to...

Interactive tool lets users see and control how automated model searches work.

Simulations suggest photonic chip could run optical neural networks 10 million times more efficiently than its electrical counterparts.

Companies use data to make a portrait of their users

Excellent variational approximations to Gaussian process posteriors have been developed which avoid the O(N3) scaling with dataset size N. They reduce the computational cost to O(NM2), with M≪N being the number of inducing variables, which summarise the process. While the computational cost seems to...

The key idea behind the unsupervised learning of disentangled representations is that real-world data is generated by a few explanatory factors of variation which can be recovered by unsupervised learning algorithms. In this paper, we provide a sober look at recent progress in the field and...

Addressing catastrophic forgetting is one of the key challenges in continual learning where machine learning systems are trained with sequential or streaming tasks. Despite recent remarkable progress in state-of-the-art deep learning, deep neural networks (DNNs) are still plagued with the...

Our increasingly technologically-mediated world continues to pose challenges for design. Considering these we suggest that the digital products and services that surround us are haunted by ‘ghosts in the machine’. These spectres bridge the physical with the digital, they broker competing...

Robots won’t hold the pens just yet, but they can help people do the work.

Why people will beat machines in recognising speech for a long time yet

Pathdoc/Shutterstock.cim

Patrycja Strycharczuk, University of Manchester

Imagine a world in which Siri always understands you, Google Translate works perfectly, and the two of them…

A new tool for predicting a person’s movement trajectory may help humans and robots work together in close proximity.

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New approach quickly finds hidden objects in dense point clouds, for use in driverless cars or work spaces with robotic assistants.

System helps machine-learning models glean training information for diagnosing and treating brain conditions.