- Stanislav Selitskiy:
"It Looks All the Same to Me": Cross-Index Training for Long-Term Financial Series Prediction. LOD (1) 2023: 348-363 - Rakesh Sengupta, Surampudi Bapi Raju, Anindya Pattanayak:
Exploring Emergent Properties of Recurrent Neural Networks Using a Novel Energy Function Formalism. LOD (1) 2023: 303-317 - Maria Sliacka, Michael N. Mistry, Roberto Calandra, Ville Kyrki, Kevin Sebastian Luck:
Co-imagination of Behaviour and Morphology of Agents. LOD (1) 2023: 318-332 - Ousmane Touat, Julian Stier, Pierre-Edouard Portier, Michael Granitzer:
GRAN Is Superior to GraphRNN: Node Orderings, Kernel- and Graph Embeddings-Based Metrics for Graph Generators. LOD (1) 2023: 430-444 - Riccardo Ughi, Eugenio Lomurno, Matteo Matteucci:
Two Steps Forward and One Behind: Rethinking Time Series Forecasting with Deep Learning. LOD (1) 2023: 463-478 - Johannes Varga, Emil Karlsson, Günther R. Raidl, Elina Rönnberg, Fredrik Lindsten, Tobias Rodemann:
Speeding Up Logic-Based Benders Decomposition by Strengthening Cuts with Graph Neural Networks. LOD (1) 2023: 24-38 - Lakshmi Sree Vindhya, R. Gnana Prasanna, Rakesh Sengupta, Anuj Shukla:
Modeling Primacy, Recency, and Cued Recall in Serial Memory Task Using On-Center Off-Surround Recurrent Neural Network. LOD (1) 2023: 405-414 - Margarita Zaleshina, Alexander Zaleshin:
Flocking Method for Identifying of Neural Circuits in Optogenetic Datasets. LOD (1) 2023: 39-52