The universal mechanism of trapping and localization of sufficiently slow-speed particles by a potential well deepening with time is established on the basis of fundamental relations of classical mechanics. Such wells may be created for a wide range...
This work focuses on AIGC detection to develop universal detectors capable of identifying various types of forgery images. Recent studies have found large pre-trained models, such as CLIP, are effective for generalizable deepfake detection along with...
Adversarial examples (AEs) are images that can mislead deep neural network (DNN) classifiers via introducing slight perturbations into original images. Recent work has shown that detecting AEs can be more effective against AEs than preventing them fr...
To meet the increasing demand of deep learning (DL) models, AI chips are employing both off-chip memory (e.g., HBM) and high-bandwidth low-latency interconnect for direct inter-core data exchange. However, it is not easy to explore the efficiency of...
Recent developments in deep reinforcement learning have been very successful in learning complex, previously intractable problems. Sample efficiency and local optimality, however, remain significant challenges. To address these challenges, novelty-dr...
Corresponding code of 'Quiros A.C., Murray-Smith R., Yuan K. Pathology GAN: Learning deep representations of cancer tissue. Proceedings of The 3rd International Conference on Medical Imaging with Deep Learning (MIDL) 2020' (⭐ 98)
In this work we develop a quantum field theory formalism for deep learning, where input signals are encoded in Gaussian states, a generalization of Gaussian processes which encode the agent's uncertainty about the input signal. We show how to represe...
A fast AI Video Generator for the GPU Poor. Supports Wan 2.1/2.2, Qwen Image, Hunyuan Video, LTX Video and Flux. - deepbeepmeep/Wan2GP
World-class human players have been outperformed in a number of complex two person games (Go, Chess, Checkers) by Deep Reinforcement Learning systems. However, owing to tractability considerations minimax regret of a learning system cannot be evaluat...
May 17, 2025 · Google DeepMind has unveiled AlphaEvolve, an evolutionary coding agent designed to autonomously discover novel algorithms and scientific solutions.
Developments in deeply virtual Compton scattering allow the direct measurements of scattering amplitudes for exchange of a highly virtual photon with fine spatial resolution. Real-space images of the target can be obtained from this information. Sp...
官网显示模型名为deepseek-V3-600BDeepseek V3的Aider代码能力排行榜正确率为48.4%，仅次于OpenAI o1，超…
Modern deep learning applications require increasingly more compute to train state-of-the-art models. To address this demand, large corporations and institutions use dedicated High-Performance Computing clusters, whose construction and maintenance ar...
Apr 1, 2025 · I encountered non-deterministic behavior when using PyTorch's DeepLabV3 model with pretrained weights. Despite fixing all random seeds, repeated executions still produce different results.
Sep 14, 2020 · Pytorch provides pre-trained deeplabv3 on Pascal dataset, I would like to train the same architecture on cityscapes. Therefore, there are different classes with respect to the Pascal VOC …
As part of the first Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI) key-science project, we aim to provide well-exposed (viz. deep) high-resolution spectra of representative stellar targets. These spectra will be made available in...
35 votes, 30 comments. I am not so experience with sounding i just wonder like.. How often you do, what size you usually do and how deep? Thank you ?
Despite recent advances, memory-augmented deep neural networks are still limited when it comes to life-long and one-shot learning, especially in remembering rare events. We present a large-scale life-long memory module for use in deep learning. The m...
官网显示模型名为deepseek-V3-600BDeepseek V3的Aider代码能力排行榜正确率为48.4%，仅次于OpenAI o1，超…
Deep learning frameworks allow researchers to create and explore Convolutional Neural Networks (CNNs) and other Deep Neural Networks (DNNs) easily, while delivering the high speed needed for …