Signal in Noise: Exploring Meaning Encoded in Random Character Sequences with Character-Aware Language Models

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State-of-the-art 2D image compression schemes rely on the power of convolutional neural networks (CNNs). Although CNNs offer promising perspectives for 2D image compression, extending such models to omnidirectional images is not straightforward. First, omn ...

As IoT applications gain widespread adoption, it becomes important to design and implement IoT protocols with security. Existing research in protocol security reveals that the majority of disclosed protocol vulnerabilities are caused by incorrectly impleme ...

Cars are some of the most security-critical consumer devices. On the one hand, owners expect rich infotainment features, including audio, hands-free calls, contact management, or navigation through their connected mobile phone. On the other hand, the infot ...

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Physically-based differentiable rendering has recently emerged as an attractive new technique for solving inverse problems that recover complete 3D scene representations from images. The inversion of shape parameters is of particular interest but also pose ...

The relation between brain functional activity and the underlying structure is complex and varies depending on the specific brain region. Recently, we used graph signal processing to introduce the structural-decoupling index (SDI), a novel metric quantifyi ...

Signal in Noise: Exploring Meaning Encoded in Random Character Sequences with Character-Aware Language Models

Chattez avec Graph Search

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Differentiable Signed Distance Function Rendering

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