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Raj Thilak Rajan on Muck Rack

Raj Thilak Rajan

As seen in: arXiv, MDPI, BIZTips
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Articles

Computer Science > Machine Learning

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By Ali Balci, Raj Thilak Rajan
| arXiv
Gaussian processes (GPs) provide a flexible framework for learning unknown functions from noisy measurements while quantifying predictive uncertainty, making them well suited for estimation in multi-agent systems. However, when measurements are collected by multiple agents, maintaining a unified GP model without centralized processing requires efficient distributed algorithms that can operate using local measurements and communication with neighboring agents.
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The 2026 R&D Tax Credit Playbook: Strengthening Claims and Capturing Value

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By Raj Thilak Rajan
| BIZTips
The research and development (R&D) tax credit remains a valuable way for companies to offset tax liability, improve cash flow, and reinvest in products, processes, and software. However, the environment for claiming the credit has changed. Evolving IRS expectations, expanded Form 6765 requirements, and the rapid adoption of AI are making R&D credit claims more data-driven, transparent, and dependent on documentation created during normal business operations.
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Computer Science > Machine Learning

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By Yogesh Kumar, Raj Thilak Rajan, Tamas Keviczky
| arXiv
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