most citedEmergent Bio-Functional Similarities in a Cortical-Spike-Train-Decoding Spiking Neural Network Facilitate Predictions of Neural Computation

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

q-bio.NC20241 cited

Decoding finger velocity from cortical spike trains with recurrent spiking neural networks

Tengjun Liu, Julia Gygax, Julian Rossbroich +3

Invasive cortical brain-machine interfaces (BMIs) can significantly improve the life quality of motor-impaired patients. Nonetheless, externally mounted pedestals pose an infection…

cs.RO2024

Towards Open-World Mobile Manipulation in Homes: Lessons from the Neurips 2023 HomeRobot Open Vocabulary Mobile Manipulation Challenge

Sriram Yenamandra, Arun Ramachandran, Mukul Khanna +42

In order to develop robots that can effectively serve as versatile and capable home assistants, it is crucial for them to reliably perceive and interact with a wide variety of obje…

q-bio.NC20232 cited

Emergent Bio-Functional Similarities in a Cortical-Spike-Train-Decoding Spiking Neural Network Facilitate Predictions of Neural Computation

Tengjun Liu, Yansong Chua, Yiwei Zhang +6

Despite its better bio-plausibility, goal-driven spiking neural network (SNN) has not achieved applicable performance for classifying biological spike trains, and showed little bio…

cs.NE20231 cited

Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition

Pengfei Sun, Ehsan Eqlimi, Yansong Chua +2

Spiking neural networks (SNN) are a promising research avenue for building accurate and efficient automatic speech recognition systems. Recent advances in audio-to-spike encoding a…

cs.CV2022

Gradient Mask: Lateral Inhibition Mechanism Improves Performance in Artificial Neural Networks

Lei Jiang, Yongqing Liu, Shihai Xiao +1

Lateral inhibitory connections have been observed in the cortex of the biological brain, and has been extensively studied in terms of its role in cognitive functions. However, in t…