7,232 research outputs found

    ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking

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    Physical intuition is pivotal for intelligent agents to perform complex tasks. In this paper we investigate the passive acquisition of an intuitive understanding of physical principles as well as the active utilisation of this intuition in the context of generalised object stacking. To this end, we provide: a simulation-based dataset featuring 20,000 stack configurations composed of a variety of elementary geometric primitives richly annotated regarding semantics and structural stability. We train visual classifiers for binary stability prediction on the ShapeStacks data and scrutinise their learned physical intuition. Due to the richness of the training data our approach also generalises favourably to real-world scenarios achieving state-of-the-art stability prediction on a publicly available benchmark of block towers. We then leverage the physical intuition learned by our model to actively construct stable stacks and observe the emergence of an intuitive notion of stackability - an inherent object affordance - induced by the active stacking task. Our approach performs well even in challenging conditions where it considerably exceeds the stack height observed during training or in cases where initially unstable structures must be stabilised via counterbalancing.Comment: revised version to appear at ECCV 201

    Choosing Truth: The Influence of Function, Institutions, and Global Culture on the Establishment of Truth and Reconciliation Commissions

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    This study explores Truth and Reconciliation Commissions (TRCs) in post-conflict societies by testing three different theoretical explanations for their establishment. The first approach is grounded in functionalist theory in which the functional needs of the post-conflict society are seen as the most influential factor. The second approach emphasizes how institutional factors constrain the options available to post-conflict societies. The last approach argues that global culture determines whether or not a post-conflict society will establish a TRC. To determine which of these approaches is accurate I used qualitative comparative analysis to compare twenty different post-conflict societies on a number of variables. My study reveals that institutional factors are more influential than functionalist factors on a country’s decision to establish a TRC. Specifically, the need for power sharing proved especially influential in both political oppression and civil war conflicts. My research also shows that the effect of international third parties is not consistent; international third party involvement does not guarantee TRC establishment. This finding suggests a greater complexity in global culture than previously thought

    Neighbouring residue effects on the ^(15)N chemical shifts of some aliphatic dipeptides

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    The ^(15)N chemical shifts of a number of simple aliphatic dipeptides have been determined in a aqueous solution and while the amine nitrogen shift is independent of the nature of the neighbouring residue, the peptide nitrogen shift shows a marked dependence upon the nature of the adjacent amino-acid

    Notes of a Jewish Women's Studies Publisher

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    Scrutinizing and De-Biasing Intuitive Physics with Neural Stethoscopes

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    Visually predicting the stability of block towers is a popular task in the domain of intuitive physics. While previous work focusses on prediction accuracy, a one-dimensional performance measure, we provide a broader analysis of the learned physical understanding of the final model and how the learning process can be guided. To this end, we introduce neural stethoscopes as a general purpose framework for quantifying the degree of importance of specific factors of influence in deep neural networks as well as for actively promoting and suppressing information as appropriate. In doing so, we unify concepts from multitask learning as well as training with auxiliary and adversarial losses. We apply neural stethoscopes to analyse the state-of-the-art neural network for stability prediction. We show that the baseline model is susceptible to being misled by incorrect visual cues. This leads to a performance breakdown to the level of random guessing when training on scenarios where visual cues are inversely correlated with stability. Using stethoscopes to promote meaningful feature extraction increases performance from 51% to 90% prediction accuracy. Conversely, training on an easy dataset where visual cues are positively correlated with stability, the baseline model learns a bias leading to poor performance on a harder dataset. Using an adversarial stethoscope, the network is successfully de-biased, leading to a performance increase from 66% to 88%

    The Second-Order Structure of Immigration Law

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    Immigration law concerns both first-order issues about the number and types of immigrants who should be admitted into a country and second-order design issues concerning the legal rules and institutions that are used to implement those first-order policy goals. The literature has focused on the first set of issues and largely neglected the second. In fact, many current controversies concern the design issues. This Article addresses the second-order dimension and argues that a central design choice all states face is whether to evaluate potential immigrants on the basis of pre-entry characteristics (the ex ante approach) or post-entry conduct (the ex post approach). The ex post system provides more information and thus results in more accurate screening than does the ex ante system, but it also may deter risk-averse applicants from making country-specific investments that benefit the host country. Focusing on this important tradeoff for states, as well as other costs and benefits of the two screening regimes, this Article evaluates America\u27s reliance on an illegal immigration system, the growth in ex post screening during the twentieth century, and America\u27s unique focus on family-related immigration

    Creating and Enforcing Norms, with Special Reference to Sanctions

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    Two central puzzles about social norms are how they are enforced and how they are created or modified. The sanctions for the violation of a norm can be categorized as automatic, guilt, shame, informational, bilateral costly, and multilateral costly. The choice of sanction is related to problems in creating and modifying norms. We use our analysis of the creation, modification, and enforcement of norms to analyze the scope of feasible government action either to promote desirable norms or to repress undesirable ones. We conclude that the difficulty of predicting the effect of such action limits its feasible scope
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