Rule extraction from recurrent neural networks: Ataxonomy and review
H Jacobsson - Neural Computation, 2005 - direct.mit.edu
Rule extraction (RE) from recurrent neural networks (RNNs) refers to finding models of the
underlying RNN, typically in the form of finite state machines, that mimic the network to a …
underlying RNN, typically in the form of finite state machines, that mimic the network to a …
Evaluation of deep learning models for multi-step ahead time series prediction
R Chandra, S Goyal, R Gupta - Ieee Access, 2021 - ieeexplore.ieee.org
Time series prediction with neural networks has been the focus of much research in the past
few decades. Given the recent deep learning revolution, there has been much attention in …
few decades. Given the recent deep learning revolution, there has been much attention in …
[HTML][HTML] Deep learning via LSTM models for COVID-19 infection forecasting in India
The COVID-19 pandemic continues to have major impact to health and medical
infrastructure, economy, and agriculture. Prominent computational and mathematical models …
infrastructure, economy, and agriculture. Prominent computational and mathematical models …
Combining symbolic and neural learning
JW Shavlik - Machine Learning, 1994 - Springer
Conclusion Connectionist machine learning has proven to be a fruitful approach, and it
makes sense to investigate systems that combine the strengths of the symbolic and …
makes sense to investigate systems that combine the strengths of the symbolic and …
[HTML][HTML] COVID-19 sentiment analysis via deep learning during the rise of novel cases
Social scientists and psychologists take interest in understanding how people express
emotions and sentiments when dealing with catastrophic events such as natural disasters …
emotions and sentiments when dealing with catastrophic events such as natural disasters …
[PDF][PDF] 基于深度学习的人体行为识别算法综述
朱煜， 赵江坤， 王逸宁， 郑兵兵 - 自动化学报, 2016 - aas.net.cn
摘要人体行为识别和深度学习理论是智能视频分析领域的研究热点, 近年来得到了学术界及工程
界的广泛重视, 是智能视频分析与理解, 视频监控, 人机交互等诸多领域的理论基础. 近年来 …
界的广泛重视, 是智能视频分析与理解, 视频监控, 人机交互等诸多领域的理论基础. 近年来 …
Input-output HMMs for sequence processing
Y Bengio, P Frasconi - IEEE Transactions on Neural Networks, 1996 - ieeexplore.ieee.org
We consider problems of sequence processing and propose a solution based on a discrete-
state model in order to represent past context. We introduce a recurrent connectionist …
state model in order to represent past context. We introduce a recurrent connectionist …
Extraction of rules from discrete-time recurrent neural networks
The extraction of symbolic knowledge from trained neural networks and the direct encoding
of (partial) knowledge into networks prior to training are important issues. They allow the …
of (partial) knowledge into networks prior to training are important issues. They allow the …
Creating advice-taking reinforcement learners
R Maclin, JW Shavlik - Machine Learning, 1996 - Springer
Learning from reinforcements is a promising approach for creating intelligent agents.
However, reinforcement learning usually requires a large number of training episodes. We …
However, reinforcement learning usually requires a large number of training episodes. We …
Constructing deterministic finite-state automata in recurrent neural networks
Recurrent neural networks that are trained to behave like deterministic finite-state automata
(DFAs) can show deteriorating performance when tested on long strings. This deteriorating …
(DFAs) can show deteriorating performance when tested on long strings. This deteriorating …