One Code to Predict Them All: Universal Encoding for Inquiry Modeling

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Photorealistic synthetic data and novel rendering techniques significantly advanced computer vision research. However, datasets focused on computer vision applications cannot be easily applied to robotics because they typically lack physics-related informa ...

Mountain regions face a variety of natural hazards that menace infrastructure and the people living in these areas. Human activity in these areas is intensifying, making hazard analysis and risk mitigation critical. Switzerland, with its densely populated ...

Faithful human performance capture and free-view rendering from sparse RGB observations is a long-standing problem in Vision and Graphics. The main challenges are the lack of observations and the inherent ambiguities of the setting, e.g. occlusions and dep ...

Image steganalysis, detecting hidden data in digital images, is essential for enhancing digital security. Traditional steganalysis methods typically rely on large, pre-labeled image datasets, which are difficult and costly to compile. To address this, this ...

Writing high-quality procedural texts is a challenging task for many learners. While example-based learning has shown promise as a feedback approach, a limitation arises when all learners receive the same content without considering their individual input ...

Deep learning (DL) has recently been proposed as a novel approach for 21cm foreground removal. Before applying DL to real observations, it is essential to assess its consistency with established methods, its performance across various simulation models, an ...

The physical mechanisms regulating the power sharing at the outer targets of L-mode double-null (DN) configurations are investigated using nonlinear, flux-driven, three-dimensional two-fluid simulations. Scans of parameters that regulate the turbulent leve ...

In this work, we provide important parameters to take into account when fabricating in-plane III-V photodetectors (PDs) integrated on silicon (Si) using template-assisted selective epitaxy (TASE). Their performance has previously been demonstrated, and her ...

Introduction: Brain-inspired computing has become an emerging field, where a growing number of works focus on developing algorithms that bring machine learning closer to human brains at the functional level. As one of the promising directions, Hyperdimensi ...

We consider a network of agents that must solve an online optimization problem from continual observation of streaming data. To this end, the agents implement a distributed cooperative strategy where each agent is allowed to perform local exchange of infor ...

Small scale ultrasonic piezoelectric actuators performance strongly depends on not well-known contact dynamics. Deep Neural Network (DNN) sees their use in physic simulation growing as their flexibility allows better performance especially when dynamics la ...

The field of text-to-video retrieval has advanced significantly with the evolution of language models and large-scale pre-training on generated caption-video pairs. Current methods predominantly focus on visual and event-based details, making retrieval lar ...

One Code to Predict Them All: Universal Encoding for Inquiry Modeling

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