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Zilong Ji

6 accepted papers

2025

Unfolding the Black Box of Recurrent Neural Networks for Path Integration

NeurIPS 2025poster

Path integration is essential for spatial navigation. Experimental studies have identified neural correlates for path integration, but exactly how the neural system accomplishes this computation remains unresolved. Here, we adopt recurrent neural networks (RNNs) trained to perform a path integration…

Cited by 0SourceScholar
2022

Adaptation Accelerating Sampling-based Bayesian Inference in Attractor Neural Networks

NeurIPS 2022accept

The brain performs probabilistic Bayesian inference to interpret the external world. The sampling-based view assumes that the brain represents the stimulus posterior distribution via samples of stochastic neuronal responses. Although the idea of sampling-based inference is appealing, it faces a crit…

Cited by 8SourcePDFScholar
2022

Oscillatory Tracking of Continuous Attractor Neural Networks Account for Phase Precession and Procession of Hippocampal Place Cells

NeurIPS 2022accept

Hippocampal place cells of freely moving rodents display an intriguing temporal organization in their responses known as `theta phase precession', in which individual neurons fire at progressively earlier phases in successive theta cycles as the animal traverses the place fields. Recent experimental…

Cited by 6SourcePDFScholar
2021

Noisy Adaptation Generates Lévy Flights in Attractor Neural Networks

NeurIPS 2021poster

Lévy flights describe a special class of random walks whose step sizes satisfy a power-law tailed distribution. As being an efficient searching strategy in unknown environments, Lévy flights are widely observed in animal foraging behaviors. Recent studies further showed that human cognitive function…

Cited by 16SourcePDFScholar
2020

An Attention-driven Two-stage Clustering Method for Unsupervised Person Re-Identification

ECCV 2020poster

The progressive clustering method and its variants, which iteratively generate pseudo labels for unlabeled data and perform feature learning, have shown great process in unsupervised person re-identification (re-id). However, they have an intrinsic problem of modeling the in-camera variability of im…

Cited by 65SourcePDFScholar
2019

Push-pull Feedback Implements Hierarchical Information Retrieval Efficiently

NeurIPS 2019poster

Experimental data has revealed that in addition to feedforward connections, there exist abundant feedback connections in a neural pathway. Although the importance of feedback in neural information processing has been widely recognized in the field, the detailed mechanism of how it works remains larg…