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Chenggang Chen

2 accepted papers

2026

Real-World Unsupervised Models Generalize to Predict Brain Responses to Out-of-Distribution Stimuli

ICML 2026spotlight

Deep neural networks currently provide the leading quantitative models of neural responses in sensory systems. However, these networks remain implausible as models of sensory development, largely because they rely on supervised training with label efficiency far exceeding that of biological learning…

Cited by 0SourceScholar
2024

Neural Embeddings Rank: Aligning 3D latent dynamics with movements

NeurIPS 2024poster

Aligning neural dynamics with movements is a fundamental goal in neuroscience and brain-machine interfaces. However, there is still a lack of dimensionality reduction methods that can effectively align low-dimensional latent dynamics with movements. To address this gap, we propose Neural Embeddings…