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Recurrent networks improve neural response prediction and provide insights into underlying cortical circuits.

, , , , , , and . CoRR, (2021)

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Improving Performance of Autoencoder-Based Network Anomaly Detection on NSL-KDD Dataset., , , , and . IEEE Access, (2021)LSTM-Autoencoder based Anomaly Detection for Indoor Air Quality Time Series Data., , , , , and . CoRR, (2022)SAM-dPCR: Real-Time and High-throughput Absolute Quantification of Biological Samples Using Zero-Shot Segment Anything Model., , , , , , , , , and 1 other author(s). CoRR, (2024)Research on Management System of Automatic Driver Decision-Making Knowledge Base for Unmanned Vehicle., , , , , , , and . Int. J. Pattern Recognit. Artif. Intell., 33 (4): 1959013:1-1959013:19 (2019)Prediction of Cleaning Loss of Combine Harvester Based on Neural Network., , , , , , , , , and . Int. J. Pattern Recognit. Artif. Intell., 34 (7): 2059021:1-2059021:14 (2020)Reconstruction-based LSTM-Autoencoder for Anomaly-based DDoS Attack Detection over Multivariate Time-Series Data., , , , , and . CoRR, (2023)MSD-Kmeans: A Novel Algorithm for Efficient Detection of Global and Local Outliers., , , and . CoRR, (2019)Spatial-temporal variations of NDVI and its response to climate in China from 2001 to 2020., , , and . Int. J. Digit. Earth, 15 (1): 1463-1484 (December 2022)A Proposed Language Model Based on LSTM., , , and . IoTaaS, volume 271 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 348-355. Springer, (2018)Automated Classification of Amyotrophic Lateral Sclerosis Using Multi-level Whole-brain Volumes from Structural Magnetic Resonance Imaging., , , and . SMC, page 830-834. IEEE, (2019)