Straightforward and approachable, this volume balances detailed first-principle derivations of novel results with insight and intuition for theorists and practitioners alike. This self-contained textbook is ideal for students and researchers interested in artificial intelligence with minimal prerequisites of ...
在布鲁塞尔大学获得博士学位后,他于1993年前往拉荷亚,加入了我的实验室,担任博士后研究员。 “通用信息最大化学习原理”(general infomax learning principle)最大限度地提高了通过网络传递的信息量。安东尼当时正在研究树突中的信号传输。树突就像细长的电缆,大脑的神经元通过附着在树突上的数以千计的突触收集信息。他...
Deep learning is one of the techniques used in machine learning. Deep learning works on the principle of extracting features from the raw data by using multiple layers for identifying different aspects relevant to input data. Deep learning techniques include convolutional network, recurrent neural netwo...
The development of artificial intelligence has not been smooth sailing so far. From the initial stage to the current deep learning stage, data, algorithms and computing power constitute the three basic elements of artificial intelligence, which jointly promote the development of artificial intelligence t...
The Free Energy Principle for Perception and Action: A Deep Learning Perspective Abstract摘要: 自由能原理及其必然结果主动推理构成了一种生物启发理论,该理论假设生物保持在世界上一组有限的优选状态中,即它们使其自由能最小化。根据这一原则,生物学习世界的生成模型,并计划未来的行动,以保持agents处于满足其偏好...
It's critical to remember that the core principle of progress in deep learning is that pushing on the 7 constraints will lead to increasingly intelligence systems. Though the scaling laws indicate that the current limiting constraints are compute and parameters, these may shift to data and energy...
【论文精读】Deep Learning and the Information Bottleneck Principle,程序员大本营,技术文章内容聚合第一站。
Deep learning (DL) for phase recovery In recent years, as an important step towards true artificial intelligence (AI), deep learning57has achieved unprecedented performance in many tasks of computer vision with the support of graphics processing units (GPUs) and large datasets. Similarly, since it...
Our guiding principle is to find a simple, relatively fast, relatively low-resource-consumption configuration that obtains a "reasonable" result. "Simple" means avoiding bells and whistles wherever possible; these can always be added later. Even if bells and whistles prove helpful down the road,...
Deep Neural Networks (DNNs) are analyzed via the theoretical framework of the information bottleneck (IB) principle. We first show that any DNN can be quantified by the mutual information between the layers and the input and output variables. Using this representation we can calculate the optimal...