MLSP-L8.5
FLEXIBLE FILTER DESIGN USING DEEP OSCILLATORY NEURAL NETWORKS
Kishore Rajendran, University of California San Diego, United States of America; Nurani Rajagopal Rohan, David Koilpillai, V. Srinivasa Chakravarthy, Indian Institute of Technology Madras, India
Session:
MLSP-L8: Spatio-Temporal Learning for Time Series Forecasting Oral
Track:
Machine Learning for Signal Processing [ML]
Location:
Room 112
Presentation Time:
Wed, 6 May, 10:20 - 10:40
Presentation
Discussion
Resources
No resources available.
Session MLSP-L8
MLSP-L8.1: SIM-MSTNET: SIM2REAL BASED MULTI-TASK SPATIOTEMPORAL NETWORK TRAFFIC FORECASTING
Hui Ma, Qingzhong Li, Jin Wang, Jie Wu, Xinjiang University, China; Shaoyu Dou, Tongji University, China; Li Feng, Bielefeld University, Germany; Xinjun Pei, Xinjiang University, China
MLSP-L8.2: CFGAN: COMPLEX FREQUENCY-DOMAIN GRAPH ATTENTION NETWORK FOR TIME SERIES FORECASTING
Zhihao Li, Lele Gao, Jinan University, China; Wenlong Qiu, Jiangxi Normal University, China; Wenyun Xiao, Jinan University, China; Hongnian Wang, North Sichuan Medical College, China
MLSP-L8.3: TSAR: Scalable Time Series Forecasting Meets Next-Scale Autoregressive Modeling
Hao Yang, Yuancheng Bian, Robert Caiming Qiu, Zenan Ling, Huazhong University of Science and Technology, China
MLSP-L8.4: A DECOMPOSITION-BASED STATE SPACE MODEL FOR MULTIVARIATE TIME-SERIES FORECASTING
Shunya Nagashima, Shuntaro Suzuki, Shuitsu Koyama, Shinnosuke Hirano, Neurogica Inc., Japan
MLSP-L8.5: FLEXIBLE FILTER DESIGN USING DEEP OSCILLATORY NEURAL NETWORKS
Kishore Rajendran, University of California San Diego, United States of America; Nurani Rajagopal Rohan, David Koilpillai, V. Srinivasa Chakravarthy, Indian Institute of Technology Madras, India
MLSP-L8.6: A DISCRETE WAVELET TRANSFORM-BASED LIGHTWEIGHT TRANSFORMER MODEL FOR INTELLIGENT FAULT DIAGNOSIS
Jiarui Zhou, Sinian Li, Justin Dauwels, Delft University of Technology, Netherlands
Contacts