Abstract: The disclosure describes one or more implementations of a neural network architecture pruning system that automatically and progressively prunes neural networks. For instance, the neural network architecture pruning system can automatically reduce the size of an untrained or previously-trained neural network without reducing the accuracy of the neural network. For example, the neural network architecture pruning system jointly trains portions of a neural network while progressively pruning redundant subsets of the neural network at each training iteration. In many instances, the neural network architecture pruning system increases the accuracy of the neural network by progressively removing excess or redundant portions (e.g., channels or layers) of the neural network. Further, by removing portions of a neural network, the neural network architecture pruning system can increase the efficiency of the neural network.

Abstract: A bipolar battery cell includes a bipolar electrode including a bipolar current collector and a cathode electrode arranged on one side of the bipolar current collector. The cathode electrode includes cathode active material for exchanging lithium ions, a first solid electrolyte, and first polytetrafluoroethylene (PTFE) fibrils. An anode electrode is arranged on an opposite side of the bipolar current collector, wherein the anode electrode includes anode active material for exchanging lithium ions, a second solid electrolyte, and second PTFE fibrils.

Abstract: An anode electrode includes a current collector and a first anode layer arranged on the current collector and comprising first anode active material. A first pre-lithiation layer is arranged on the first anode layer. A second anode layer arranged on the first pre-lithiation layer and comprising second anode active material.

Abstract: A battery cell includes an anode electrode comprising a first current collector. Anode active material is arranged on a first surface of the first current collector and is configured to exchange lithium ions. The anode active material comprises silicon. Empty spaces are formed in the anode active material in a predetermined pattern. A solid electrolyte layer is arranged adjacent to the anode electrode. A cathode electrode comprises a second current collector and cathode active material configured to exchange lithium ions and arranged adjacent to the solid electrolyte layer.

Abstract: A pixel structure, an array substrate, a display panel and a display device. The pixel structure includes a gate line (10), a data line (20), a gate (30), a first electrode (40), a second electrode (50), and a third electrode (60); the gate (30) is connected to the gate line (10); the first electrode (40) is connected to the data line (20); and the second electrode (50) has a first portion and a second portion that are distributed in the extending direction of the second electrode, wherein the first portion of the second electrode (50) cooperates with the first electrode (40) and the gate (30) to form a first thin film transistor, and the second portion of the second electrode (50) cooperates with the third electrode (60) and the gate (30) to form a second thin film transistor.

Abstract: A method for determining a regulation range of pumping power of a three-machine pumped storage unit is provided. The method includes: obtaining a first parameter set of pumping measurement parameters for characterizing the three-machine pumped storage unit and determining a pumping process efficiency; determining a first relational expression based on the pumping process efficiency and a design efficiency of a pumped storage power station and establishing a second relational expression; and determining a third relational expression based on power absorbed by a power grid and the second relational expression and determining a fourth relational expression, where the fourth relational expression reflects the regulation range of the pumping power of the three-machine pumped storage unit. The method for determining the regulation range of the pumping power of the three-machine pumped storage unit is proposed according to unit characteristics and operating economy of the power station.

Abstract: Provided herein are novel compounds, for example, compounds having a Formula (I), or a pharmaceutically acceptable N salt thereof. Also provided herein are methods of preparing the compounds and methods of using the compounds, for example, in inhibiting TYK2, and/or function of IL-12, IL-23 and/or INF-alpha, and/or in treating various associated diseases or disorders.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via multi-layered scene completion techniques facilitated by artificial intelligence. For instance, in some embodiments, the disclosed systems receive a digital image portraying a first object and a second object against a background, where the first object occludes a portion of the second object. Additionally, the disclosed systems pre-process the digital image to generate a first content fill for the portion of the second object occluded by the first object and a second content fill for a portion of the background occluded by the second object. After pre-processing, the disclosed systems detect one or more user interactions to move or delete the first object from the digital image. The disclosed systems further modify the digital image by moving or deleting the first object and exposing the first content fill for the portion of the second object.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

Abstract: The disclosure relates to the field of electronic materials, and in particular to a composite film of fluorinated polybenzoxazole (6FPBO) and triple-shelled mesoporous silica hollow spheres, and to its preparation and use. The composite film comprises fluorinated polybenzoxazole as a matrix and amino-functionalized triple-shelled mesoporous silica hollow spheres which are dispersed in the fluorinated polybenzoxazole matrix. A mass ratio of (amino-functionalized triple-shelled mesoporous silica hollow spheres)/(fluorinated polybenzoxazole) is 1/100 to 5/100. The composite film has excellent thermal stability and a lower dielectric constant.

Abstract: A battery includes positive and negative current collectors and a plurality of bipolar electrodes arranged in a stack between the positive and negative current collectors. The positive and negative current collectors and the stack of the plurality of bipolar electrodes are folded in an S-shape.

Abstract: Apparatus, systems, articles of manufacture, and methods for robot movement are disclosed. An example robot movement apparatus includes a sequence generator to generate a sequence of context variable vectors and policy variable vectors. The context variable vectors are related to a movement target, and the policy variable vectors are related to a movement trajectory. The example apparatus includes a calculator to calculate an upper policy and a loss function based on the sequence. The upper policy is indicative of a robot movement, and the loss function is indicative of a degree to which a movement target is met. The example apparatus also includes a comparator to determine if the loss function satisfies a threshold and an actuator to cause the robot to perform the robot movement of the upper policy when the loss function satisfies the threshold.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

Abstract: Embodiments of the present invention relate to the field of communications methods and technologies, and in particular, to a transmission method and apparatus. The transmission method includes: generating, by a first device, a sequence based on one or more transmission parameters, where the one or more transmission parameters include at least one of the following: a time domain resource type, transmission waveform indication information, subcarrier spacing indication information, device type information, service type indication information, multiple-input multiple-output MIMO parameter information, duplex mode indication information, control channel format indication information, and transmission carrier indication information; generating to-be-transmitted information by using the sequence; and sending the to-be-transmitted information. According to the transmission method and apparatus in the embodiments of the present invention, a new transmission error check mechanism is provided.