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Publication search results
found 151 matches
- 2024
- Priscila Grecov, Ankitha Nandipura Prasanna, Klaus Ackermann, Sam Campbell, Deborah A. Scott, Dan I. Lubman, Christoph Bergmeir:
Probabilistic Causal Effect Estimation With Global Neural Network Forecasting Models. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4999-5013 (2024) - Ke Su, Hang Su, Chongxuan Li, Jun Zhu, Bo Zhang:
Probabilistic Neural-Symbolic Models With Inductive Posterior Constraints. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2667-2679 (2024) - Farhad Pourkamali-Anaraki, Jamal F. Husseini, Scott E. Stapleton:
Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning. CoRR abs/2402.13945 (2024) - 2023
- Yilei Qiu, Shunzhen Wang, Shuai Zhang, Jiyuan Xu:
A novel gated dual convolutional neural network model with autoregressive method and attention mechanism for probabilistic load forecasting. Appl. Intell. 53(17): 20256-20271 (2023) - Audrey Olivier, Sevin Mohammadi, Andrew W. Smyth, Matt Adams:
Bayesian neural networks with physics-aware regularization for probabilistic travel time modeling. Comput. Aided Civ. Infrastructure Eng. 38(18): 2614-2631 (2023) - Arun Singh Yadav, Surendra Kumar, Girija Rani Karetla, Juan Carlos Cotrina-Aliaga, José Luis Arias-Gonzáles, Vinod Kumar, Satyajee Srivastava, Reena Gupta, Sufyan Ibrahim, Rahul Paul, Nithesh Naik, Babita Singla, Nisha S. Tatkar:
A Feature Extraction Using Probabilistic Neural Network and BTFSC-Net Model with Deep Learning for Brain Tumor Classification. J. Imaging 9(1): 10 (2023) - Ziyu Gan, Wei Sun, Kaimin Liao, Xuan Yang:
Probabilistic Modeling for Image Registration Using Radial Basis Functions: Application to Cardiac Motion Estimation. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7324-7338 (2023) - Jungang Lou, Yunliang Jiang, Qing Shen, Ruiqin Wang, Zechao Li:
Probabilistic Regularized Extreme Learning for Robust Modeling of Traffic Flow Forecasting. IEEE Trans. Neural Networks Learn. Syst. 34(4): 1732-1741 (2023) - Xiaoqi Wang, Han-Wei Shen:
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks. ICLR 2023 - Martina Pastorino, Gabriele Moser, Sebastiano B. Serpico, Josiane Zerubia:
Classification of Multimission SAR Images Based on Probabilistic Graphical Models and Convolutional Neural Networks. IGARSS 2023: 1420-1423 - Jiayuan Chen, Xiang Zhang, Yinfei Xu, Tianli Zhao, Renjie Xie, Wei Xu:
Understanding and Improving Deep Graph Neural Networks: A Probabilistic Graphical Model Perspective. CoRR abs/2301.10536 (2023) - Man Yao, Yuhong Chou, Guangshe Zhao, Xiawu Zheng, Yonghong Tian, Bo Xu, Guoqi Li:
Probabilistic Modeling: Proving the Lottery Ticket Hypothesis in Spiking Neural Network. CoRR abs/2305.12148 (2023) - Boyao Li, Alexandar J. Thomson, Matthew M. Engelhard, David Page:
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models. CoRR abs/2305.17583 (2023) - 2022
- Elie Azeraf:
Classification avec des modèles probabilistes génératifs et des réseaux de neurones. Applications au traitement des langues naturelles. (Classification with generative probabilistic models and neural networks. Applications to natural language processing). Polytechnic Institute of Paris, Palaiseau, France, 2022 - Cui Wang, Xuedong Wang, Yongdong Zhu:
Hazard Assessment of Debris Flow Based on Infinite Irrelevance Method and Probabilistic Neural Network Coupling Model. IEEE Access 10: 36823-36833 (2022) - Javad Forough, Saeedeh Momtazi:
Sequential credit card fraud detection: A joint deep neural network and probabilistic graphical model approach. Expert Syst. J. Knowl. Eng. 39(1) (2022) - Jun Chen, Junhui Zhao:
Generating synthetic wind speed scenarios using artificial neural networks for probabilistic analysis of hybrid energy systems. Int. J. Model. Identif. Control. 41(3): 183-192 (2022) - Elif Köksal Ersöz, Pascal Chossat, Martin Krupa, Frédéric Lavigne:
Dynamic branching in a neural network model for probabilistic prediction of sequences. J. Comput. Neurosci. 50(4): 537-557 (2022) - Keita Mori, Naohiro Yamauchi, Haoyu Wang, Ken Sato, Yu Toyoshima, Yuichi Iino:
Probabilistic generative modeling and reinforcement learning extract the intrinsic features of animal behavior. Neural Networks 145: 107-120 (2022) - Akira Taniguchi, Ayako Fukawa, Hiroshi Yamakawa:
Hippocampal formation-inspired probabilistic generative model. Neural Networks 151: 317-335 (2022) - Tadahiro Taniguchi, Hiroshi Yamakawa, Takayuki Nagai, Kenji Doya, Masamichi Sakagami, Masahiro Suzuki, Tomoaki Nakamura, Akira Taniguchi:
A whole brain probabilistic generative model: Toward realizing cognitive architectures for developmental robots. Neural Networks 150: 293-312 (2022) - Marek Kciuk, Tomasz Bijok, Grazia Lo Sciuto:
Design and Modeling of Intelligent Building Office and Thermal Comfort Based on Probabilistic Neural Network. SN Comput. Sci. 3(6): 485 (2022) - Jia Liu, Wenhua Zhang, Fang Liu, Liang Xiao:
A Probabilistic Model Based on Bipartite Convolutional Neural Network for Unsupervised Change Detection. IEEE Trans. Geosci. Remote. Sens. 60: 1-14 (2022) - Martina Pastorino, Gabriele Moser, Sebastiano B. Serpico, Josiane Zerubia:
Semantic Segmentation of Remote-Sensing Images Through Fully Convolutional Neural Networks and Hierarchical Probabilistic Graphical Models. IEEE Trans. Geosci. Remote. Sens. 60: 1-16 (2022) - Zheng Chai, Chunhui Zhao, Biao Huang, Hongtian Chen:
A Deep Probabilistic Transfer Learning Framework for Soft Sensor Modeling With Missing Data. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7598-7609 (2022) - Zhengjue Wang, Bo Chen, Hao Zhang, Hongwei Liu:
Unsupervised Hyperspectral and Multispectral Images Fusion Based on Nonlinear Variational Probabilistic Generative Model. IEEE Trans. Neural Networks Learn. Syst. 33(2): 721-735 (2022) - Yajie Bao, Kimberly J. Chan, Ali Mesbah, Javad Mohammadpour Velni:
Learning-based Adaptive-Scenario-Tree Model Predictive Control with Probabilistic Safety Guarantees Using Bayesian Neural Networks. ACC 2022: 3260-3265 - Xinjue Wang, Esa Ollila, Sergiy A. Vorobyov:
Graph Neural Network Sensitivity Under Probabilistic Error Model. EUSIPCO 2022: 2146-2150 - Xinjue Wang, Esa Ollila, Sergiy A. Vorobyov:
Graph Neural Network Sensitivity Under Probabilistic Error Model. CoRR abs/2203.07831 (2022) - Madhurima Panja, Uttam Kumar, Tanujit Chakraborty:
An Interpretable Probabilistic Autoregressive Neural Network Model for Time Series Forecasting. CoRR abs/2204.09640 (2022)
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