More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory. - James B. Simon; Dhruva Karkada; Nikhil Ghosh; Mikhail Belkin (CoRR, 2023)

The Eigenlearning Framework: A Conservation Law Perspective on Kernel Ridge Regression and Wide Neural Networks. - James B. Simon; Madeline Dickens; Dhruva Karkada; Michael Robert DeWeese (Trans. Mach. Learn. Res., 2023)

More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory. - James B. Simon; Dhruva Karkada; Nikhil Ghosh; Mikhail Belkin (ICLR, 2024)

The lazy (NTK) and rich (μP) regimes: a gentle tutorial. - Dhruva Karkada (CoRR, 2024)

Solvable Dynamics of Self-Supervised Word Embeddings and the Emergence of Analogical Reasoning. - Dhruva Karkada; James B. Simon; Yasaman Bahri; Michael Robert DeWeese (CoRR, 2025)

On the Emergence of Linear Analogies in Word Embeddings. - Daniel J. Korchinski; Dhruva Karkada; Yasaman Bahri; Matthieu Wyart (CoRR, 2025)

Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks. - Daniel Kunin; Giovanni Luca Marchetti; Feng Chen; Dhruva Karkada; James B. Simon; Michael Robert DeWeese; Surya Ganguli; Nina Miolane (CoRR, 2025)