The presence of mutual information in the research of deep learning has grown significantly. It has been proven that mutual information can be a good objective function to build a robust deep learning model. Most of the researches utilize estimation...
Powered by the rising popularity of deep learning techniques on smartphones, on-device deep learning models are being used in vital fields like finance, social media, and driving assistance. Because of the transparency of the Android platform and t...
Parallel developments in neuroscience and deep learning have led to mutually productive exchanges, pushing our understanding of real and artificial neural networks in sensory and cognitive systems. However, this interaction between fields is less dev...
支持GPT-4/Claude/Deepseek/Sakura等大语言模型的Galgame自动化翻译解决方案 Automated translation solution for visual novels supporting GPT-4/Claude/Deepseek/Sakura (⭐ 1992)
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We present the Blue Jay survey, a Cycle-1 JWST program aimed at studying the stellar and gas content of galaxies at Cosmic Noon. The survey consists of deep spectroscopy for 153 targets observed over two pointings in the COSMOS field using the NIRSpe...
The diffusion of deepfake technologies has sparked serious concerns about its potential misuse across various domains, prompting the urgent need for robust detection methods. Despite advancement, many current approaches prioritize short-term gains at...
work on deep learning. The four (including Jürgen Schmidhuber ) are sometimes referred to as the "Godfathers of AI" and "Godfathers of Deep Learning". LeCun
Retrospectively gated cine (retro-cine) MRI is the clinical standard for cardiac functional analysis. Deep learning (DL) based methods have been proposed for the reconstruction of highly undersampled MRI data and show superior image quality and magni...
Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation…
In this white paper, we review five top considerations for selecting locations of the fields of the Roman High-latitude Time Domain Survey. Based on these considerations, we recommend Akari Deep Field South (ADFS)/Euclid Deep Field South (EDFS) in th...
We address the problem to tackle the very similar objects like Chihuahua or muffin problem to recognize at least in human vision level. Our regular deep structured machine learning still does not solve it. We saw many times for about year in our comm...
Backdoor attacks have emerged as a critical security threat against deep neural networks in recent years. The majority of existing backdoor attacks focus on targeted backdoor attacks, where trigger is strongly associated to specific malicious behavio...
The deep image prior showed that a randomly initialized network with a suitable architecture can be trained to solve inverse imaging problems by simply optimizing it's parameters to reconstruct a single degraded image. However, it suffers from two pr...
Bothragonus swanii, the rockhead, deep-pitted poacher or deep-pitted sea-poacher, is a species of fish in the family Agonidae. It was described by Franz
Purpose: To assess the capability of deep convolutional neural networks to classify anatomical location and projection from a series of 48 standard views of racehorse limbs. Materials and Methods: 9504 equine pre-import radiographs were used to tra...
Gemini是谷歌推出的多模态AI基座模型，深度整合谷歌生态，具备领先的多模态处理能力，支持百万级token长文本和Canvas模式，适用于企业级AI应用开发。 Google DeepMind刚发布的Gemini 2.5。 …
We perform an exploratory study of higher twist contributions to deep inelastic scattering. We estimate the size of two major sources of higher twist, namely absorptive corrections and the vector meson dominance (VMD) contribution. We find that the...
We develop a deep learning model of multi-period mortgage risk and use it to analyze an unprecedented dataset of origination and monthly performance records for over 120 million mortgages originated across the US between 1995 and 2014. Our estimators...
Implicit-depth models such as Deep Equilibrium Networks have recently been shown to match or exceed the performance of traditional deep networks while being much more memory efficient. However, these models suffer from unstable convergence to a solut...