Chaitanya Kapoor — accepted AI-conference papers

2026

Unbalanced Soft-Matching Distance For Neural Representational Comparison With Partial Unit Correspondence

Chaitanya Kapoor, Alex H Williams, Meenakshi Khosla

ICLR 2026poster

Representational similarity metrics typically force all units to be matched, making them susceptible to noise and outliers common in neural representations. We extend the soft-matching distance to a partial optimal transport setting that allows some neurons to remain unmatched, yielding rotation-sen…

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2025

Bridging Critical Gaps in Convergent Learning: How Representational Alignment Evolves Across Layers, Training, and Distribution Shifts

Chaitanya Kapoor, Sudhanshu Srivastava, Meenakshi Khosla

NeurIPS 2025poster

Understanding convergent learning---the degree to which independently trained neural systems---whether multiple artificial networks or brains and models---arrive at similar internal representations---is crucial for both neuroscience and AI. Yet, the literature remains narrow in scope---typically exa…

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