Mufeng Tang

According to our database, Mufeng Tang authored at least 10 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Task success in trained spiking neural network models coincides with emergence of cross-stimulus-modulated inhibition.

Yuqing Zhu, Chadbourne M. B. Smith, Tarek Jabri, Mufeng Tang, Franz Scherr, Jason N. MacLean

Biol. Cybern., February, 2026

2025

Bidirectional predictive coding.

Gaspard Oliviers, Mufeng Tang, Rafal Bogacz

CoRR, May, 2025

Neural Associative Skill Memories for safer robotics and modelling human sensorimotor repertoires.

Pranav Mahajan, Mufeng Tang, T. Ed Li, Ioannis Havoutis, Ben Seymour

CoRR, May, 2025

Predictive Coding Model Detects Novelty on Different Levels of Representation Hierarchy.

T. Ed Li, Mufeng Tang, Rafal Bogacz

Neural Comput., 2025

Benchmarking Predictive Coding Networks - Made Simple.

Luca Pinchetti, Chang Qi, Oleh Lokshyn, Cornelius Emde, Amine M'Charrak, Mufeng Tang, Simon Frieder, Bayar Menzat, Gaspard Oliviers, Rafal Bogacz, Thomas Lukasiewicz, Tommaso Salvatori

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Predictive coding networks for temporal prediction.

Beren Millidge, Mufeng Tang, Mahyar Osanlouy, Nicol S. Harper, Rafal Bogacz

PLoS Comput. Biol., 2024

Benchmarking Predictive Coding Networks - Made Simple.

Luca Pinchetti, Chang Qi, Oleh Lokshyn, Gaspard Olivers, Cornelius Emde, Mufeng Tang, Amine M'Charrak, Simon Frieder, Bayar Menzat, Rafal Bogacz, Thomas Lukasiewicz, Tommaso Salvatori

CoRR, 2024

2023

Recurrent predictive coding models for associative memory employing covariance learning.

Mufeng Tang, Tommaso Salvatori, Beren Millidge, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz

PLoS Comput. Biol., 2023

Sequential Memory with Temporal Predictive Coding.

Mufeng Tang, Helen Barron, Rafal Bogacz

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Biologically Plausible Training Mechanisms for Self-Supervised Learning in Deep Networks.

Mufeng Tang, Yibo Yang, Yali Amit

Frontiers Comput. Neurosci., 2022