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Jul 25, 2024 · DeepSeek-R1 Release ⚡ Performance on par with OpenAI-o1 ? Fully open-source model & technical report ? Code and models are released under the MIT License: Distill & commercialize …
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20 hours ago · A small AI lab called DeepSeek dropped something that made the entire AI industry go quiet. They released DeepSeek-R1: a 671-billion-parameter reasoning model that matched or …
arxiv.org/abs/1509.01344v1
We present a new image of the 5.5 GHz radio emission from the extended Chandra Deep Field South. Deep radio observations at 5.5 GHz were obtained in 2010 and presented in the first data release. A further 76 hours of integration has since been obtain...
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Does “burrow nose-deep” literally mean “dig in / bury deeply,” or have other figurative meanings like intimacy? To me “burrow nose-deep” in episodes of Emily Dickinson and Obama’s replacement of …
arxiv.org/abs/2004.12538v2
Recently deep neural networks demonstrate competitive performances in classification and regression tasks for many temporal or sequential data. However, it is still hard to understand the classification mechanisms of temporal deep neural networks. In...
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deepseek-r1 DeepSeek-R1 is a family of open reasoning models with performance approaching that of leading models, such as O3 and Gemini 2.5 Pro.
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20 hours ago · A small AI lab called DeepSeek dropped something that made the entire AI industry go quiet. They released DeepSeek-R1: a 671-billion-parameter reasoning model that matched or …
arxiv.org/abs/1905.07187v1
Despite the huge empirical success of deep learning, theoretical understanding of neural networks learning process is still lacking. This is the reason, why some of its features seem "mysterious". We emphasize two mysteries of deep learning: generali...
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DeepSeek-R1 is a family of open reasoning models with performance approaching that of leading models, such as O3 and Gemini 2.5 Pro. DeepSeek-R1 has received a minor version upgrade to …
arxiv.org/abs/2308.03953v2
Deep learning has emerged as an effective solution for addressing the challenges of short-term voltage stability assessment (STVSA) in power systems. However, existing deep learning-based STVSA approaches face limitations in adapting to topological c...
arxiv.org/abs/2511.17307v3
The data storage requirements for deep spectral line observations with next-generation radio interferometers like the Australian Square Kilometre Array Pathfinder (ASKAP) and the Square Kilometre Array (SKA) are extremely challenging. The default str...
arxiv.org/abs/2410.02285v3
The next generation of radio astronomy telescopes are challenging existing data analysis paradigms, as they have an order of magnitude more antennas and larger bandwidth. Foremost amongst these are deep spectral line surveys, because these have the l...
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DEEP definition: extending far down from the top or surface. See examples of deep used in a sentence.
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arxiv.org/abs/2405.06473v1
The technology of autonomous driving is currently attracting a great deal of interest in both research and industry. In this paper, we present a deep learning dual-model solution that uses two deep neural networks for combined braking and steering in...
arxiv.org/abs/2005.03461v1
In recent years, deep neural networks have been applied to obtain high performance of prediction, classification, and pattern recognition. However, the weights in these deep neural networks are difficult to be explained. Although a linear regression...
arxiv.org/abs/2302.00150v1
The current deep learning model is of a single-grade, that is, it learns a deep neural network by solving a single nonconvex optimization problem. When the layer number of the neural network is large, it is computationally challenging to carry out su...
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