217 citations · 1.4k across the 33 of their papers we have counts for
5 papers · 1 filter
A geometric bound on the efficiency of irreversible thermodynamic cycles
Adam G. Frim, Michael R. DeWeese
Stochastic thermodynamics has revolutionized our understanding of heat engines operating in finite time. Recently, numerous studies have considered the optimal operation of thermod…
Stochastic optimization for learning quantum state feedback control
Ethan N. Evans, Ziyi Wang, Adam G. Frim +2
High fidelity state preparation represents a fundamental challenge in the application of quantum technology. While the majority of optimal control approaches use feedback to improv…
The Eigenlearning Framework: A Conservation Law Perspective on Kernel Regression and Wide Neural Networks
James B. Simon, Madeline Dickens, Dhruva Karkada +1
We derive simple closed-form estimates for the test risk and other generalization metrics of kernel ridge regression (KRR). Relative to prior work, our derivations are greatly simp…
Optimal finite-time Brownian Carnot engine
Adam G. Frim, Michael R. DeWeese
Recent advances in experimental control of colloidal systems have spurred a revolution in the production of mesoscale thermodynamic devices. Functional "textbook" engines, such as…
Reverse Engineering the Neural Tangent Kernel
James B. Simon, Sajant Anand, Michael R. DeWeese
The development of methods to guide the design of neural networks is an important open challenge for deep learning theory. As a paradigm for principled neural architecture design,…