
Reintroducing StraightThrough Estimators as Principled Methods for Stochastic Binary Networks
Training neural networks with binary weights and activations is a challe...
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Path SampleAnalytic Gradient Estimators for Stochastic Binary Networks
In networks with binary activations and or binary weights the training b...
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MPLP++: Fast, Parallel Dual BlockCoordinate Ascent for Dense Graphical Models
Dense, discrete Graphical Models with pairwise potentials are a powerful...
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Taxonomy of Dual BlockCoordinate Ascent Methods for Discrete Energy Minimization
We consider the maximumaposteriori inference problem in discrete graph...
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Belief Propagation Reloaded: Learning BPLayers for Labeling Problems
It has been proposed by many researchers that combining deep neural netw...
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Stochastic Normalizations as Bayesian Learning
In this work we investigate the reasons why Batch Normalization (BN) imp...
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Feedforward Uncertainty Propagation in Belief and Neural Networks
We propose a feedforward inference method applicable to belief and neur...
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Normalization of Neural Networks using Analytic Variance Propagation
We address the problem of estimating statistics of hidden units in a neu...
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Generative learning for deep networks
Learning, taking into account full distribution of the data, referred to...
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Scalable Full Flow with Learned Binary Descriptors
We propose a method for large displacement optical flow in which local m...
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EndtoEnd Training of Hybrid CNNCRF Models for Stereo
We propose a novel and principled hybrid CNN+CRF model for stereo estima...
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Complexity of Discrete Energy Minimization Problems
Discrete energy minimization is widelyused in computer vision and machi...
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Joint MBestDiverse Labelings as a Parametric Submodular Minimization
We consider the problem of jointly inferring the Mbest diverse labeling...
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Solving Dense Image Matching in RealTime using DiscreteContinuous Optimization
Dense image matching is a fundamental lowlevel problem in Computer Visi...
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Maximum Persistency via Iterative Relaxed Inference with Graphical Models
We consider the NPhard problem of MAPinference for undirected discrete...
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Higher Order Maximum Persistency and Comparison Theorems
We address combinatorial problems that can be formulated as minimization...
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Partial Optimality by Pruning for MAPInference with General Graphical Models
We consider the energy minimization problem for undirected graphical mod...
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Curvature Prior for MRFbased Segmentation and Shape Inpainting
Most image labeling problems such as segmentation and image reconstructi...
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On Partial Opimality by Auxiliary Submodular Problems
In this work, we prove several relations between three different energy ...
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