Abzal Kutynbetov

Breaking the Memory Horizon of Spiking Neural Networks via Autonomous Phase-Space Distillation and Hierarchical Sleep

Spiking Neural Networks (SNNs) offer order-of-magnitude energy efficiency improvements over dense Transformers through event-driven, sparse computation. However, recurrent SNNs suffer from a fundamental physical limitation: the fading memory horizon. Due to passive membrane dissi...

Breaking the Memory Horizon of Spiking Neural Networks via Autonomous Phase-Space Distillation and Hierarchical Sleep

Spiking Neural Networks (SNNs) offer order-of-magnitude energy efficiency improvements over dense Transformers through event-driven, sparse computation. However, recurrent SNNs suffer from a fundamental physical limitation: the fading memory horizon. Due to passive membrane dissi...