6 accepted papers
Training deep spiking neural networks (SNNs) remains challenging due to sharp loss landscapes and temporal inconsistency caused by surrogate gradients. To address these challenges, we propose a unified framework: adaptive and asymmetric surrogate gradients (A$^2$SG). The adaptive gradients adjust an…
Most research on multimodal open-domain dialogue agents has focused on pretraining and multi-task learning using additional rich datasets beyond a given target dataset. However, methods for exploiting these additional datasets can be quite limited in real-world settings, creating a need for more eff…
Spiking neural networks (SNNs) that mimic information transmission in the brain can energy-efficiently process spatio-temporal information through discrete and sparse spikes, thereby receiving considerable attention. To improve accuracy and energy efficiency of SNNs, most previous studies have focus…
Surface electromyograms (sEMG), are records of electrical signals generated by muscles, and have long been used to indicate the motions intended by humans to enable interactions between a robot and a human. To support not only the diverse movements in human daily living but also the task of increasi
Microneedle insertion is useful for elucidating the processes in living cells and their organelles. However, mechanical puncture by the needle causes traumatic damage to the cell. As a less invasive process, we have developed intracellular needle insertion using femtosecond laser cell ablation. To q…
Dynamic motion of human shows kinematic aspects related to storing elastic energy in skeletal muscle. This results from joint stiffness modulation and as a consequence, countermovement which is opposite to the intended motion is observed. We propose a segmentation algorithm based on a hidden semi-Ma…