Abstract: Implementations provide for use of spherical random features for polynomial kernels and large-scale learning. An example method includes receiving a polynomial kernel, approximating the polynomial kernel by generating a nonlinear randomized feature map, and storing the nonlinear feature map. Generating the nonlinear randomized feature map includes determining optimal coefficient values and standard deviation values for the polynomial kernel, determining an optimal probability distribution of vector values for the polynomial kernel based on a sum of Gaussian kernels that use the optimal coefficient values, selecting a sample of the vectors, and determining the nonlinear randomized feature map using the sampled vectors.

Abstract: An apparatus includes a gauge cutter, a lead impression block (LIB), a locking pin, and a locking device. The gauge cutter has a gauge cutter tubular body, a gauge cutter head, and an orifice. The LIB has an LIB body and an LIB head. The LIB is fixed in a first position within the orifice of the gauge cutter by being connected to an inner circumferential surface of the gauge cutter tubular body using a shear pin. The locking pin is disposed around the LIB body. The locking device is disposed around the inner circumferential surface of the gauge cutter tubular body and is configured to mate with the locking pin to hold the LIB in a second position within the gauge cutter. The second position includes a portion of the LIB body located within the orifice and the LIB head located outside of the orifice.

Abstract: The present disclosure provides systems and methods that include or otherwise leverage use of a multiscale quantization model that is configured to provide a quantized dataset. In particular, the multiscale quantization model can receive and perform vector quantization of a first dataset. The multiscale quantization model can generate a residual dataset based at least in part on a result of the vector quantization. The multiscale quantization model can apply a rotation matrix to the residual dataset to generate a rotated residual dataset that includes a plurality of rotated residuals. The multiscale quantization model can perform reparameterization of each rotated residual in the rotated residual dataset into a direction component and a scale component. The multiscale quantization model can perform product quantization of the direction components of the plurality of rotated residuals, and perform scalar quantization of the scale components of the plurality of rotated residuals.

Abstract: Generally, the present disclosure is directed to systems and methods that perform adaptive optimization with improved convergence properties. The adaptive optimization techniques described herein are useful in various optimization scenarios, including, for example, training a machine-learned model such as, for example, a neural network. In particular, according to one aspect of the present disclosure, a system implementing the adaptive optimization technique can, over a plurality of iterations, employ an adaptive learning rate while also ensuring that the learning rate is non-increasing.

Abstract: A system for setting a wellhead pressure after a through tubing bridge plug is installed in a wellbore includes a slickline unit, a static bottomhole pressure gauge, and a pressure setting unit. The slickline unit includes the static bottomhole pressure gauge. The static bottomhole pressure gauge includes internal memory that stores a measured bottomhole pressure. The pressure setting unit sets a wellhead pressure based on the measured bottomhole pressure stored in the internal memory of the static bottomhole pressure gauge. A related method includes installing a through tubing bridge plug in a wellbore, deploying a slickline unit into the wellbore, wherein the slickline unit includes a pressure gauge, measuring bottomhole pressure with the pressure gauge, and setting a wellhead pressure based on the measured bottomhole pressure.

Abstract: Provided are systems and methods that improve the computational efficiency of Transformers or other attention-based neural networks or machine learning models by re-using a number of attention scores between layers and/or heads of the model. To reduce the computational cost of self-attention-based models while achieving comparable or even superior results, example aspects of the present disclosure propose a novel architecture that reuses attention scores computed in one layer in one or multiple subsequent layers.

Abstract: A system includes a flexi-string having a first lateral end, a second lateral end, and an outer diameter. The outer diameter defines an outer circumferential surface, and the outer diameter is smaller than an inner diameter of a casing shoe. The system further includes an anchor disposed on the outer circumferential surface of the first lateral end, where the anchor interacts with the casing shoe, or a last joint of casing, to hold the first lateral end of the flexi-string within the casing shoe. The system also has centralizers located between the first lateral end and the second lateral end of the flexi-string. The centralizers are configured to center the flexi-string within the casing shoe and the washout section. Finally, the system includes a roller guide for lowering the flexi-string inside the casing shoe and to a depth below the washout section of the well.

Abstract: A caliper pig for detecting geometrical deformation of a pipeline is disclosed. The caliper pig includes a body and a first sensor arm assembly. The first sensor arm assembly includes a primary caliper sensor ring adapted to be mounted on the body. Further, the first sensor arm assembly includes a plurality of sensor arms adapted circumferentially distributed on the primary caliper sensor ring. Each of the plurality of sensor arms includes a sensing arm adapted to be in contact with an internal surface of the pipeline and a pair of magnets adapted to rotate along the sensing arm. Each of the plurality of sensor arms includes a sensing unit configured to detect a change in magnetic field based on the movement of the sensing arm. The sensing unit is configured to generate an output indicative of an angle of deflection of the sensing arm while traversing on the internal surface of the pipeline.

Abstract: Generally, the present disclosure is directed to systems and methods that perform adaptive optimization with improved convergence properties. The adaptive optimization techniques described herein are useful in various optimization scenarios, including, for example, training a machine-learned model such as, for example, a neural network. In particular, according to one aspect of the present disclosure, a system implementing the adaptive optimization technique can, over a plurality of iterations, employ an adaptive learning rate while also ensuring that the learning rate is non-increasing.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for accounting for long-tail training data.

Abstract: Computer-based method and system for urban planning of a facility are described herein. The method and system facilitate a user, without any hard knowledge of geographic information system (GIS) to perform quick geo-spatial analysis with a fully automated, single step, and single input process including automatically determining one or more criteria corresponding to the facility based on the facility type defined by the user, automatically performing data analysis on a plurality of data-sets, automatically determining and presenting at least one suitable site within the geographic area for the facility based on the data analysis.

Abstract: The present disclosure provides systems and methods that include or otherwise leverage use of a multiscale quantization model that is configured to provide a quantized dataset. In particular, the multiscale quantization model can receive and perform vector quantization of a first dataset. The multiscale quantization model can generate a residual dataset based at least in part on a result of the vector quantization. The multiscale quantization model can apply a rotation matrix to the residual dataset to generate a rotated residual dataset that includes a plurality of rotated residuals. The multiscale quantization model can perform reparameterization of each rotated residual in the rotated residual dataset into a direction component and a scale component. The multiscale quantization model can perform product quantization of the direction components of the plurality of rotated residuals, and perform scalar quantization of the scale components of the plurality of rotated residuals.

Abstract: A method includes receiving, by a computing device, training data to train a neural network, wherein the training data comprises a plurality of inputs and a plurality of corresponding labels. The method also includes mapping, by a representation learner of the neural network, the plurality of inputs to a plurality of feature vectors. The method additionally includes training a kernelized classification layer of the neural network to perform nonlinear classification of an input feature vector into one of a plurality of classes, wherein the kernelized classification layer is based on a kernel which enables the nonlinear classification, and wherein the kernel is selected from a space of positive definite kernels based on application of a nonlinear softmax loss function to the plurality of feature vectors and the plurality of corresponding labels. The method further includes outputting a trained neural network comprising the representation learner and the trained kernelized classification layer.

Abstract: Embodiments of the invention relate to a membrane-electrode assembly comprising a membrane structure with an anode layer, a cathode layer, and a membrane layer, wherein the membrane layer is positioned between the anode layer and the cathode layer. The membrane-electrode assembly furthermore comprises an anode-side gas-diffusion layer arranged on the anode layer and a cathode-side gas-diffusion layer arranged on the cathode layer. Furthermore, at least one of the anode-side gas-diffusion and the cathode-side gas-diffusion layers has a structure on the side facing away from the membrane structure. According to some embodiments, the structure comprises a plurality of columns for forming a laterally-open flow field, wherein the columns have support surfaces for supporting a bipolar plate.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for multi-stage computationally-efficient inference using a first and second neural network.

Abstract: The present invention relates to a method of making of hydrocarbon soluble metal composition comprising of one or more metals of group VIB of the periodic table, wherein the metal having 4+ oxidation state predominantly forms highly active metal sulfide catalyst for hydro-conversion of heavy oil feedstocks in liquid phase. More particularly, present invention relates to a hydrocarbon soluble metal composition comprising of reaction products of a metal source, a lipophilic phenolic acid, a surfactant and an organophosphorus compound. The present invention also provides a one-pot process for preparation of the hydrocarbon soluble metal composition comprising reacting a metal source, a lipophilic phenolic acid, a surfactant, an organophosphorus compound and water to obtain a reaction product and drying the reaction product to obtain the hydrocarbon soluble metal composition.

Abstract: A fuel cell stack is provided comprising membrane electrode assemblies and bipolar plates for supplying the membrane electrode assemblies with operating media and coolant, wherein a first bipolar plate comprises flow pathways having path depths that are different from path depths of corresponding flow pathways of a second bipolar plate. Moreover, a vehicle with a fuel cell system having such a fuel cell stack is provided.

Abstract: A systems and method for providing various improvements in the computing time and accuracy for finding items using a hybrid vector space inner-product search are described.

Abstract: Techniques of indexing a database and processing a query involve decomposing the residual term according to a projection matrix that is based on a given direction v. For example, for each database element of a partition, the residual for that database element is split into a component parallel to a given direction and a component perpendicular to that direction. The parallel component lies in a one-dimensional subspace spanned by the direction and may be efficiently quantized with a scalar quantization. The perpendicular component is quantized using multiscale quantization techniques. The quantized residual components and the center elements of each partition define the indexed database. Upon receipt of a query from a user, the inner products of q with the residual may be computed efficiently using the quantized residual components. From these inner products, the database elements that are most similar to the query are selected and returned to the user.

Abstract: This invention relates to production of low sulfur MARPOL compliant bunker fuel oil and distillates using high sulfur residue, low sulfur residue and/or blend of high and low sulfur residue feed stock. The invention also describes a method for production of a cutterstock stream having a lower paraffin and higher aromatic content than a feed stream using a paraffin separation section and its blending to produce bunker fuel.