Deep learning has a wide range of applications in many industries, such as image classification, image recognition, and speech recognition. DLI provides several functions
A Topology-Aware Performance Prediction Model for Distributed Deep Learning on GPU Clustersieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9378252 一种基于GPU集群的分布式深度学习的拓扑感知性能预测模型 Abstract 1.Introdiction 分布式深度学习执行在GPU等设备的集群上,其中一个关键就是良好的GPU连接,以...
Even though the depth of a Deep Learning model increases its expressiveness, increasing depth also makes it more difficult to optimise the network weights due to gradients vanishing or exploding. In [48] Residual Networks have been proposed to solve these problems. By adding a skip connection from...
The research team utilized a Convolutional Long Short-Term Memory (ConvLSTM) neural network to construct a seasonal-scale Antarctic sea ice prediction model. Their forecast indicated that Antarctic sea ice would remain close to historical lows in February 2024, but there was less indication of it r...
“How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model”这个工作主要探讨:为何GPT模型能够通过预训练获得数学能力。具体而言,用的是类似“The war lasted from the year 17YY to the year 17”的Prompt,GPT模型可以做到输出的Next Token的年份数字XX大于YY...
强化学习-4:无模型预测 model-free prediction 对于Env来说,属于MP,但是不是参数已知的MDP 比如元组中a、s、P的关系不确定 or 未知 Prediction -> Control Evaluation -> Optimization 蒙特卡洛法 Monte-Carlo learning 基于大数定律: \(V(s) -> V_\pi(s)\) as \(N(s)->\infty\)...
demonstrated that the EBVNet’s performance was superior (AUROC: 0.895 [95% CI: 0.84, 0.95] vs 0.819 [95% CI: 0.73, 0.90]) in detecting EBV status from histopathologic slides, indicating the better effectiveness of our deep learning model in screening patients for the confirmation of EBV ...
Deep Interest Network ResNet xDeepFM AFM(Attentional FM) Transformer FiBiNET 代码使用tf.estimator构建, 数据存储为tfrecord格式(字典,key:value), 采用tf.Dataset API, 加快IO速度,支持工业级的应用。特征工程定义在input_fn,模型定义在model_fn,实现特征和模型代码分离,特征工程代码只用修改input_fn,模型代码只用...
AMPlify is an attentive deep learning model for antimicrobial peptide prediction. Dependencies Python 3.6 Keras 2.2.4 Tensorflow 1.12 Numpy <1.17 Pandas Scikit-learn Biopython h5py <3 Installation Create a newcondaenvironment: conda create -n amplify python=3.6 ...
For example, more customized in-class learning activities or interventions could be implemented to improve the students' adaptive behavior, which possibly could result in better school attendance. Figure 3 SA prediction performance of the proposed models. (a) Multivariate model outperforms the ...