Abstract: Implicit neural representation (INR) has been a powerful paradigm for effectively compressing time-varying volumetric data. However, the optimization process can span days or even weeks due ...
David Adler, 32, defines himself as a radical skeptic. The political scientist and economist was born and raised in Los Angeles. And, since 2020, has been the co-general coordinator of Progressive ...
Growing up, Melissa Shultz sometimes felt like she had two fathers. One version of her dad, she told me, was playful and quick to laugh. He was a compelling storyteller who helped shape her career as ...
Abstract: The increasing complexity of traffic dynamics has underscored the necessity for advanced traffic safety description and analysis, challenging the efficacy of current methodologies in ...
Abstract: Deep supervised learning algorithms typically require a large volume of labeled data to achieve satisfactory performance. However, the process of collecting and labeling such data can be ...
Abstract: This research article presents a comparison between two mainstream Deep Reinforcement Learning (DRL) algorithms, Asynchronous Advantage Actor-Critic (A3C) and Proximal Policy Optimization ...
Abstract: Combining quantum computers with classical compute power has become a standard means for developing algorithms and heuristics that are, eventually, supposed to beat any purely classical ...
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