Abstract: A securing device (10) for securing a first object (320) relative to a second object (322) includes a device body (12) having a cross-sectional area, and which is formed from a material so that the device body (12) exhibits elongation of between six hundred percent and eight hundred percent. A ratio of the elongation (in percent) to the cross-sectional area (in square millimeters) is between approximately 5:1 and 10:1. The device body (12) is also formed from the material so that the device body (12) exhibits a tensile strength of between four thousand five hundred kPa and nine thousand three hundred kPa. A ratio of the tensile strength (in kPa) to the cross-sectional area (in square millimeters) is between approximately 50:1 and 85:1. The material that forms the device body (12) has an average kinetic coefficient of friction of between approximately 1.35 and 1.60 relative to itself. The material that forms the device body (12) can include thermoplastic elastomers, and can further include styrene.

Abstract: An improved system architecture uses a Generative Adversarial Network (GAN) including a specialized generator neural network to generate multiple resolution output images. The system produces a latent space representation of an input image. The system generates a first output image at a first resolution by providing the latent space representation of the input image as input to a generator neural network comprising an input layer, an output layer, and a plurality of intermediate layers and taking the first output image from an intermediate layer, of the plurality of intermediate layers of the generator neural network. The system generates a second output image at a second resolution different from the first resolution by providing the latent space representation of the input image as input to the generator neural network and taking the second output image from the output layer of the generator neural network.

Abstract: Systems and methods generate a filtering function for editing an image with reduced attribute correlation. An image editing system groups training data into bins according to a distribution of a target attribute. For each bin, the system samples a subset of the training data based on a pre-determined target distribution of a set of additional attributes in the training data. The system identifies a direction in the sampled training data corresponding to the distribution of the target attribute to generate a filtering vector for modifying the target attribute in an input image, obtains a latent space representation of an input image, applies the filtering vector to the latent space representation of the input image to generate a filtered latent space representation of the input image, and provides the filtered latent space representation as input to a neural network to generate an output image with a modification to the target attribute.

Abstract: Systems and methods train an encoder neural network for fast and accurate projection into the latent space of a Generative Adversarial Network (GAN). The encoder is trained by providing an input training image to the encoder and producing, by the encoder, a latent space representation of the input training image. The latent space representation is provided as input to the GAN to generate a generated training image. A latent code is sampled from a latent space associated with the GAN and the sampled latent code is provided as input to the GAN. The GAN generates a synthetic training image based on the sampled latent code. The sampled latent code is provided as input to the encoder to produce a synthetic training code. The encoder is updated by minimizing a loss between the generated training image and the input training image, and the synthetic training code and the sampled latent code.

Abstract: An improved system architecture uses a pipeline including a Generative Adversarial Network (GAN) including a generator neural network and a discriminator neural network to generate an image. An input image in a first domain and information about a target domain are obtained. The domains correspond to image styles. An initial latent space representation of the input image is produced by encoding the input image. An initial output image is generated by processing the initial latent space representation with the generator neural network. Using the discriminator neural network, a score is computed indicating whether the initial output image is in the target domain. A loss is computed based on the computed score. The loss is minimized to compute an updated latent space representation. The updated latent space representation is processed with the generator neural network to generate an output image in the target domain.

Abstract: An improved system architecture uses a pipeline including an encoder and a Generative Adversarial Network (GAN) including a generator neural network to generate edited images with improved speed, realism, and identity preservation. The encoder produces an initial latent space representation of an input image by encoding the input image. The generator neural network generates an initial output image by processing the initial latent space representation of the input image. The system generates an optimized latent space representation of the input image using a loss minimization technique that minimizes a loss between the input image and the initial output image. The loss is based on target perceptual features extracted from the input image and initial perceptual features extracted from the initial output image. The system outputs the optimized latent space representation of the input image for downstream use.

Abstract: Systems and methods dynamically adjust an available range for editing an attribute in an image. An image editing system computes a metric for an attribute in an input image as a function of a latent space representation of the input image and a filtering vector for editing the input image. The image editing system compares the metric to a threshold. If the metric exceeds the threshold, then the image editing system selects a first range for editing the attribute in the input image. If the metric does not exceed the threshold, a second range is selected. The image editing system causes display of a user interface for editing the input image comprising an interface element for editing the attribute within the selected range.

Abstract: Systems and methods train and apply a specialized encoder neural network for fast and accurate projection into the latent space of a Generative Adversarial Network (GAN). The specialized encoder neural network includes an input layer, a feature extraction layer, and a bottleneck layer positioned after the feature extraction layer. The projection process includes providing an input image to the encoder and producing, by the encoder, a latent space representation of the input image. Producing the latent space representation includes extracting a feature vector from the feature extraction layer, providing the feature vector to the bottleneck layer as input, and producing the latent space representation as output. The latent space representation produced by the encoder is provided as input to the GAN, which generates an output image based upon the latent space representation. The encoder is trained using specialized loss functions including a segmentation loss and a mean latent loss.

Abstract: The invention provides compounds of formula (I): wherein X is and the variables are defined in the specification, or a pharmaceutically-acceptable salt thereof, that are useful as JAK kinase inhibitors. The invention also provides pharmaceutical compositions comprising such compounds, methods of using such compounds to treat respiratory diseases, and processes and intermediates useful for preparing such compounds.

Abstract: The invention provides compounds of formula (I): where the variables are defined in the specification, or a pharmaceutically-acceptable salt thereof, that are useful as JAK kinase inhibitors. The invention also provides pharmaceutical compositions comprising such compounds, methods of using such compounds to treat respiratory diseases, and processes and intermediates useful for preparing such compounds.

Abstract: Described is a self-massage device including a massage board with multiple connected indentations formed along the length of the massage board. The self-massage device also includes one or more massage heads having a top portion formed to contact a portion of a user's body, and a bottom portion having a protrusion formed to be removably inserted into one or more of the connected indentations in the massage board via a pressure mechanism.

Abstract: Compounds of the formula (I): wherein A and B together represent an optionally substituted, fused aromatic ring; X can be NRX or CRXRY; if X?NRX then n is 1 or 2 and if X?CRXRY then n is 1; RX is selected from the group consisting of H, optionally substituted C1-20 alkyl, C5-20 aryl, C3-20 heterocyclyl, amido, thioamido, ester, acyl, and sulfonyl groups; RY is selected from H, hydroxy, amino; or RX and RY may together form a spiro-C3-7 cycloalkyl or heterocyclyl group; RC1 and RC2 are both hydrogen, or when X is CRXRY, RC1, RC2, RX and RY, together with the carbon atoms to which they are attached, may form an optionally substituted fused aromatic ring; and R1 is selected from H and halo.

Abstract: Images can be edited to include features similar to a different target image. An unconditional generative adversarial network (GAN) is employed to edit features of an initial image based on a constraint determined from a target image. The constraint used by the GAN is determined from keypoints or segmentation masks of the target image, and edits are made to features of the initial image based on keypoints or segmentation masks of the initial image corresponding to those of the constraint from the target image. The GAN modifies the initial image based on a loss function having a variable for the constraint. The result of this optimization process is a modified initial image having features similar to the target image subject to the constraint determined from the identified keypoints or segmentation masks.

Abstract: A system and method for managing thermal energy of a vehicle having a battery and an electric propulsion system are provided. The system monitors a current battery temperature, calculates an actual average battery temperature, and compares the calculated actual average battery temperature to a target lifetime battery temperature. If the actual average battery temperature is greater than the target lifetime battery temperature, and the current battery temperature is greater than the target lifetime battery temperature, the system cools the battery to below the current battery temperature. However, if the actual average battery temperature is less than the target lifetime battery temperature, and the current battery temperature is greater than the target lifetime battery temperature, the system delays cooling the battery. Therefore, the system may avoid expending energy to cool the battery in certain conditions.

Abstract: The invention provides compounds of formula (I): which contain a 4-membered heterocyclic amide, where the variables are defined in the specification, or a pharmaceutically-acceptable salt thereof, that are useful as JAK kinase inhibitors. The invention also provides pharmaceutical compositions comprising such compounds, methods of using such compounds to treat respiratory diseases, and processes and intermediates useful for preparing such compounds.

Abstract: Images can be edited to include features similar to a different target image. An unconditional generative adversarial network (GAN) is employed to edit features of an initial image based on a constraint determined from a target image. The constraint used by the GAN is determined from keypoints or segmentation masks of the target image, and edits are made to features of the initial image based on keypoints or segmentation masks of the initial image corresponding to those of the constraint from the target image. The GAN modifies the initial image based on a loss function having a variable for the constraint. The result of this optimization process is a modified initial image having features similar to the target image subject to the constraint determined from the identified keypoints or segmentation masks.

Abstract: A securing device (10) for securing a first object (320) relative to a second object (322) includes a device body (12) having a cross-sectional area, and which is formed from a material so that the device body (12) exhibits elongation of between six hundred percent and eight hundred percent. A ratio of the elongation (in percent) to the cross-sectional area (in square millimeters) is between approximately 5:1 and 10:1. The device body (12) is also formed from the material so that the device body (12) exhibits a tensile strength of between four thousand five hundred kPa and nine thousand three hundred kPa. A ratio of the tensile strength (in kPa) to the cross-sectional area (in square millimeters) is between approximately 50:1 and 85:1. The material that forms the device body (12) has an average kinetic coefficient of friction of between approximately 1.35 and 1.60 relative to itself. The material that forms the device body (12) can include thermoplastic elastomers, and can further include styrene.

Abstract: The invention provides compounds of formula (I): where the variables are defined in the specification, or a pharmaceutically-acceptable salt thereof, that are useful as JAK kinase inhibitors. The invention also provides pharmaceutical compositions comprising such compounds and methods of using such compounds to treat respiratory diseases.

Abstract: The invention provides compounds of formula (I): wherein X is and the variables are defined in the specification, or a pharmaceutically-acceptable salt thereof, that are useful as JAK kinase inhibitors. The invention also provides pharmaceutical compositions comprising such compounds, methods of using such compounds to treat respiratory diseases, and processes and intermediates useful for preparing such compounds.