backpropagation through time

Pseudo-Spiking Neurons: A Noise-Based Training Framework for Heterogeneous-Latency Spiking Neural Networks AAAI 2026 Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation NeurIPS 2024 Balanced Resonate-and-Fire Neurons ICML 2024 Embarrassingly Simple Dataset Distillation ICLR 2024 Exploiting Symmetric Temporally Sparse BPTT for Efficient RNN Training AAAI 2024 Exploring the Promise and Limits of Real-Time Recurrent Learning ICLR 2024 Harnessing Manycore Processors with Distributed Memory for Accelerated Training of Sparse and Recurrent Models AAAI 2024 NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks ICML 2024 Stabilizing Backpropagation Through Time to Learn Complex Physics ICLR 2024 Time-Efficient Reinforcement Learning with Stochastic Stateful Policies ICLR 2024 Unconditional stability of a recurrent neural circuit implementing divisive normalization NeurIPS 2024 Efficient recurrent architectures through activity sparsity and sparse back-propagation through time ICLR 2023 Evaluating Long-Term Memory in 3D Mazes ICLR 2023 Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks JMLR 2023 SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks NeurIPS 2023 Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks ICCV 2023 Training biologically plausible recurrent neural networks on cognitive tasks with long-term dependencies NeurIPS 2023 Biologically-plausible backpropagation through arbitrary timespans via local neuromodulators NeurIPS 2022 Learning Sampling Distributions for Model Predictive Control CoRL 2022 Online Training Through Time for Spiking Neural Networks NeurIPS 2022 Oscillatory Fourier Neural Network: A Compact and Efficient Architecture for Sequential Processing AAAI 2022 Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods ICLR 2022 Faster Policy Learning with Continuous-Time Gradients L4DC 2021 Practical Real Time Recurrent Learning with a Sparse Approximation ICLR 2021 Training Recurrent Neural Networks via Forward Propagation Through Time ICML 2021