Alper Kayabasi — accepted AI-conference papers

2026

The Surprising Effectiveness of Noise Pretraining for Implicit Neural Representations

Kushal Vyas, Alper Kayabasi, Daniel Kim, Vishwanath Saragadam, Ashok Veeraraghavan, Guha Balakrishnan

CVPR 2026

The approximation and convergence properties of implicit neural representations (INRs) are known to be highly sensitive to parameter initialization strategies. While several data-driven initialization methods demonstrate significant improvements over standard random sampling, the reasons for their s

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2025

Bias for Action: Video Implicit Neural Representations with Bias Modulation

Alper Kayabasi, Anil Kumar Vadathya, Guha Balakrishnan, Vishwanath Saragadam

CVPR 2025poster

We propose a new continuous video modeling framework based on implicit neural representations (INRs) called ActINR. At the core of our approach is the observation that INRs can be considered as a learnable dictionary, with the shapes of the basis functions governed by the weights of the INR, and the…

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