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stat.ML2025
VIKING: Deep variational inference with stochastic projections
Samuel G. Fadel, Hrittik Roy, Nicholas Krämer +5
Variational mean field approximations tend to struggle with contemporary overparametrized deep neural networks. Where a Bayesian treatment is usually associated with high-quality p…
cs.LG2025
Matrix-Free Least Squares Solvers: Values, Gradients, and What to Do With Them
Hrittik Roy, Søren Hauberg, Nicholas Krämer
This paper argues that the method of least squares has significant unfulfilled potential in modern machine learning, far beyond merely being a tool for fitting linear models. To re…
math.CA2025
Uniform decoupling for convex curves
Hrit Roy
Using a high/low argument, we prove a universal decoupling estimate with constant for general convex curves in the plane. These curves have no additional regul…