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Found 7 papers, 0 papers with code
A meta-probabilistic-programming language for bisimulation of probabilistic and non-well-founded type systems
We introduce a formal meta-language for probabilistic programming, capable of expressing both programs and the type systems in which they are embedded.
Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives
Here, we offer a framework for representing and learning flexible PAC-Bayes bounds as stochastic programs using DPP-based methods.
Rank Projection Trees for Multilevel Neural Network Interpretation
A variety of methods have been proposed for interpreting nodes in deep neural networks, which typically involve scoring nodes at lower layers with respect to their effects on the output of higher-layer nodes (where lower and higher layers are closer to the input and output layers, respectively).
Dense Semantic Image Segmentation with Objects and Attributes
The concepts of objects and attributes are both important for describing images precisely, since verbal descriptions often contain both adjectives and nouns (e. g. "I see a shiny red chair').
A Tiered Move-making Algorithm for General Non-submodular Pairwise Energies
The algorithm converges to a local minimum for any general pairwise potential, and we give a theoretical analysis of the properties of the algorithm, characterizing the situations in which we can expect good performance.
ImageSpirit: Verbal Guided Image Parsing
This allows us to formulate the image parsing problem as one of jointly estimating per-pixel object and attribute labels from a set of training images.
Mesh Based Semantic Modelling for Indoor and Outdoor Scenes
We then define a CRF over this mesh, which is able to capture the consistency of geometric properties of the objects present in the scene.
