Convolutional RNNs

RNN: Recurrent Neural Network

Follow this topic Ask about this topic

Momentum

1 paper in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Jul 13Week of Sep 28

Latest papers 17

All topics

IRENE: A Convolutional GRU Ensemble Model for Radar Precipitation Nowcasting over Italy
Sep 15, 2026Alessandro Camilletti, Gabriele Franch, Elena Tomasi +1Convolutional RNNs Precipitation Forecasting
Fondazione Bruno Kessler
State of Health Estimation using Convolutional and Bidirectional LSTM Neural Networks tuned by Bayesian Optimization
Aug 31, 2026Panagiotis Eleftheriadis, Foivos Georgios Kyrgios, Sonia LevaConvolutional RNNs Lithium-Ion Batteries
Department of Energy, Politecnico di Milano, via Lambruschini 4a, 20156 Milano, Italy
A Hybrid Framework of Vision Transformer and Gated Recurrent Unit for Detection of Mosquito Diseases
Aug 12, 2026Danial Sharifrazi, Saadat Behzadi, Nouman Javed +3Convolutional RNNs Animal Behavior Analysis
Predictive Failure Detection in Network Hardware Using Thermal Imaging and Deep Learning with Sensor Fusion
Aug 5, 2026Ashly JosephConvolutional RNNs Predictive Maintenance
Independent Researcher
Deep Learning CNN and Recurrence Analysis for Alpha Gamma EEG Biomarkers in Fragile X Syndrome
Aug 1, 2026Zag ElSayed, Payton Siekierski, Jack Yanchen Liu +1Convolutional RNNs Electroencephalography
School of Information Technology (SoIT), University of Cincinnati, Ohio, USA · Division of Child and Adolescent Psychiatry Cincinnati Children’s Hospital Medical Center, Ohio, USA
Benchmarking ConvLSTM for One-Day-Ahead IMDAA Rainfall-Field Prediction across Four Indian Cities
Jul 29, 2026Tanmay Ghosh, Shaurabh Anand, Rakesh Gomaji Nannewar +1Convolutional RNNs Precipitation Forecasting
National Institute of Advanced Studies, Indian Institute of Science Campus, Bengaluru, India. · School of Development, Azim Premji University, Bengaluru, India. · Complex Systems Programme, National Institute of Advanced Studies, Indian Institute of Science Campus, Bengaluru, India.
Physics-Informed CNN-LSTM for Street-Scale Urban Flood Prediction: Reconciling Aggregate Accuracy and Street-Level Plausibility
Jul 27, 2026Luc DCosta, Yidi Wang, Jonathan L. Goodall +1Convolutional RNNs Flood Inundation Mapping
Chandra Robot Autonomy Lab, Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA · Link Lab, Multidisciplinary Research Center, University of Virginia, Charlottesville, VA 22904, USA · Hydroinformatics Research Group, Department of Civil and Environmental Engineering, University of Virginia, Charlottesville, VA 22904, USA
Exploratory Analysis of Deep Learning Models for Forecasting Meteorological Parameters in the Agricultural Sector
Jul 11, 2026Piotr Sikora, Sotirios KontogiannisConvolutional RNNs Multivariate Time Series Forecasting
Faculty of Technical Physics, Information Technology and Applied Mathematics Lodz Universtiy of Technlogy · MicroComputer Systems Laboratory Dept. of Mathematics University of Ioannina
Speaker head orientation estimation with a single microphone array using phase spectrogram features
Jul 2, 2026Balint Turi, Archontis Politis, Parthasaarathy Sudarsanam +1Convolutional RNNs Spatial Audio
Audio Research Group, Tampere University, Finland
Urdu Katib Handwritten Dataset: A Historical Document Dataset for Offline Urdu Handwritten Text Recognition with CRNN-Based Baseline Evaluation
Jun 17, 2026Ramza Basharat, Muhammad Usman AliConvolutional RNNs Recurrent Neural Networks
Department of Computer Science, University of Gujrat, Pakistan · Department of Computer Science, University of Gujrat, Gujrat, Punjab, Pakistan
Growing a Neural Network in Breadth, Depth, and Time
May 24, 2026Eivinas Butkus, Kedar Garzón Gupta, Nikolaus KriegeskorteConvolutional RNNs Dynamic Neural Networks
1Columbia University · 2NSF AI Institute for Artificial and Natural Intelligence
CBANet: A Compact Attention-Based CNN-BiLSTM Network for Aggressive Driving Event Detection
May 22, 2026Hanadi Alhamdan, Ghadah Alosaimi, Amir Atapour-Abarghouei +1Class-Imbalanced Learning Convolutional RNNs
Department of Computer Science, Princess Nourah bint Abdulrahman University, Saudi Arabia · Department of Computer Science, Durham University, UK · Department of Computer Science, Imam Mohammad Ibn Saud Islamic University, Saudi Arabia
A Distribution Matching Approach to Neural Piano Transcription with Optimal Transport
May 17, 2026Weixing Wei, Raynaldi Lalang, Dichucheng Li +1Convolutional RNNs Automatic Music Transcription
Graduate School of Informatics, Kyoto University, Japan · Graduate School of Engineering, Kyoto University, Japan · Independent Researcher, Hong Kong, China
Understanding Cross-Language Transfer Improvements in Low-Resource HTR: The Role of Sequence Modeling
May 7, 2026Sana Al-azzawi, Chang Liu, Nudrat Habib +2Convolutional RNNs Recurrent Neural Networks
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering , Luleå, Sweden · Luleá University of Technology, Department of Computer Science, Electrical and Space Engineering , Luleå, Sweden
A Comparative Study of PyCaret AutoML and CNN-BiLSTM for Binary Hate Speech Detection in Indonesian Twitter
May 6, 2026Tanty Widiyastuti, Mayada, Adisty Syawalda Ariyanto +3Convolutional RNNs Hate Speech Detection
Department of Data Science Institut Teknologi Sumatera (ITERA) Lampung, Indonesia · Department of Informatics Institut Teknologi Sumatera (ITERA) Lampung, Indonesia
Neural surrogates for crystal growth dynamics with variable supersaturation: explicit vs. implicit conditioning
Apr 23, 2026Matteo Rigoni, Daniele Lanzoni, Francesco Montalenti +1Neural Surrogate Modeling Convolutional RNNs
Dept. of Materials Science, University of Milano-Bicocca, 20125 Milano, Italy · Dept. of Physics, University of Genova, 16146 Genova, Italy
Combining Convolution and Delay Learning in Recurrent Spiking Neural Networks
Apr 17, 2026Lúcio Folly Sanches Zebendo, Eleonora Cicciarella, Michele RossiConvolutional RNNs Efficient Neural Network Inference
University of Padova, Department of Information Engineering · Department of Mathematics “Tullio Levi Civita” at the University of Padova, Italy

Sep 15, 2026, cs.LGJ/K move · Enter open · S save

IRENE: A Convolutional GRU Ensemble Model for Radar Precipitation Nowcasting over Italy

Alessandro Camilletti, Gabriele Franch, Elena Tomasi, Marco Cristoforetti

Fondazione Bruno Kessler

Convolutional RNNs Precipitation Forecasting Probabilistic Forecasting Precipitation Nowcasting

Open paper AskPDF arXiv

We present IRENE (Italian Radar Ensemble Nowcasting Experiment), a deep learning model for probabilistic short-range precipitation nowcasting over the Italian domain at \SI{1}{km} spatial and 5 min temporal resolution. IRENE adopts an encoder--forecaster architecture built on multi-scale Convolutional Gated Recurrent Units (ConvGRUs), trained on the national radar composite produced by the Italian Civil Protection Department (DPC). An importance-sampling scheme focuses training on precipitation-relevant events, while the almost-fair Continuous Ranked Probability Score (afCRPS) is adopted as the primary probabilistic loss function. Two additional training configurations are proposed: an adversarial (GAN) variant, IRENE-GAN, designed to improve the spatial sharpness of the generated forecasts, and a spectrally constrained variant, IRENE-GAN-RAPSD, in which the adversarial objective is complemented by an explicit penalty on the radially averaged power spectral density. The three configurations are evaluated against the stochastic extrapolation method STEPS and the pre-trained deep learning model DGMR. All IRENE configurations attain a lower Continuous Ranked Probability Score than both benchmarks at every lead time and rank histograms closer to uniformity, indicating better probabilistic skill and ensemble calibration. In terms of ensemble-mean mean absolute error the advantage is confined to the first 90 min, beyond which the strongly damped DGMR fields and, to a lesser extent, STEPS become competitive. Spectral analysis shows that the adversarial training removes the progressive loss of small-scale variance exhibited by IRENE, at the cost of an excess of fine-scale power at long lead times that the spectral penalty only partially controls.

Momentum

Related topics

Latest papers 17