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cs.LG2026
Sequential Reservoir Computing for Efficient High-Dimensional Spatiotemporal Forecasting
Ata Akbari Asanjan, Filip Wudarski, Daniel O'Connor +4
Forecasting high-dimensional spatiotemporal systems remains computationally challenging for recurrent neural networks (RNNs) and long short-term memory (LSTM) models due to gradien…
cs.LG2020
RBM-Flow and D-Flow: Invertible Flows with Discrete Energy Base Spaces
Daniel O'Connor, Walter Vinci
Efficient sampling of complex data distributions can be achieved using trained invertible flows (IF), where the model distribution is generated by pushing a simple base distributio…