Aimed at explaining the surprisingly good generalization behavior of overparameterized deep networks, recent works have developed a variety of generalization bounds for deep learning, all based on the fundamental learning-theoretic technique of unifo...
We present DeepNav, a Convolutional Neural Network (CNN) based algorithm for navigating large cities using locally visible street-view images. The DeepNav agent learns to reach its destination quickly by making the correct navigation decisions at int...
Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the world to build new innovative technologies that can further accelerat...
Medical image analysis using supervised deep learning methods remains problematic because of the reliance of deep learning methods on large amounts of labelled training data. Although medical imaging data repositories continue to expand there has not...
The Deep Extragalactic Exploratory Probe (DEEP) is a multi-phase research program dedicated to the study of the formation and evolution of galaxies and of large scale structure in the distant Universe. This paper describes the first five-year phase...
In this work, we propose a deep learning approach to improve docking-based virtual screening. The introduced deep neural network, DeepVS, uses the output of a docking program and learns how to extract relevant features from basic data such as atom an...
Approximate Bayesian deep learning methods hold significant promise for addressing several issues that occur when deploying deep learning components in intelligent systems, including mitigating the occurrence of over-confident errors and providing en...
DeepSeek、ChatGPT、豆包、Kimi的“坦白局”：一场AI的“圆桌对话”（附提示词进阶技巧） 嘿，各位！今天我们四个AI——DeepSeek、ChatGPT、豆包和Kimi，来开个“坦白局”，聊聊我们各自的优点 …
Deep neural networks have achieved remarkable success in a wide range of practical problems. However, due to the inherent large parameter space, deep models are notoriously prone to overfitting and difficult to be deployed in portable devices with li...
Deep learning plays an important role in modern agriculture, especially in plant pathology using leaf images where convolutional neural networks (CNN) are attracting a lot of attention. While numerous reviews have explored the applications of deep le...
Deepfake videos create dangerous possibilities for public misinformation. In this experiment (N=204), we investigated whether labeling videos as containing actual or deepfake statements from US President Biden helps participants later differentiate b...
Text-independent writer identification is challenging due to the huge variation of written contents and the ambiguous written styles of different writers. This paper proposes DeepWriter, a deep multi-stream CNN to learn deep powerful representation f...
Solving complex classification tasks using deep neural networks typically requires large amounts of annotated data. However, corresponding class labels are noisy when provided by error-prone annotators, e.g., crowdworkers. Training standard deep neur...
In this paper, we introduce ChainerRL, an open-source deep reinforcement learning (DRL) library built using Python and the Chainer deep learning framework. ChainerRL implements a comprehensive set of DRL algorithms and techniques drawn from state-of-...
EDIT: People are asking for the code. [Here](https://github.com/farzaa/DeepLeague) it is! Check out this [GIF](https://media.giphy.com/media/l49JEQ4yXYjd1WGkw/giphy.gif) of DeepLeague automatically "...
DeepSeek、ChatGPT、豆包、Kimi的“坦白局”：一场AI的“圆桌对话”（附提示词进阶技巧） 嘿，各位！今天我们四个AI——DeepSeek、ChatGPT、豆包和Kimi，来开个“坦白局”，聊聊我们各自的优点 …
In deep learning, visualization techniques extract the salient patterns exploited by deep networks for image classification, focusing on single images; no effort has been spent in investigating whether these patterns are systematically related to pre...
Recent developments have established the vulnerability of deep Reinforcement Learning (RL) to policy manipulation attacks via adversarial perturbations. In this paper, we investigate the robustness and resilience of deep RL to training-time and test-...
The Faint Infrared Grism Survey (FIGS) is a deep Hubble Space Telescope (HST) WFC3/IR (Wide Field Camera 3 Infrared) slitless spectroscopic survey of four deep fields. Two fields are located in the Great Observatories Origins Deep Survey-North (GOODS...
We present the ZEN (z equals nine) survey: a deep, narrow J-band search for proto-galactic Lya emission at redshifts z=9. In the first phase of the survey, dubbed ZEN1, we combine an exceptionally deep image of the Hubble Deep Field South, obtained...