154 citations · 374 across the 20 of their papers we have counts for
7 papers · 1 filter
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis +1
Flow-based models are powerful tools for designing probabilistic models with tractable density. This paper introduces Convex Potential Flows (CP-Flow), a natural and efficient para…
Inverse design of dissipative quantum steady-states with implicit differentiation
Rodrigo A. Vargas-Hernández, Ricky T. Q. Chen, Kenneth A. Jung +1
Inverse design of a property that depends on the steady-state of an open quantum system is commonly done by grid-search type of methods. In this paper we present a new methodology…
Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering
Ricky T. Q. Chen, Dami Choi, Lukas Balles +2
Standard first-order stochastic optimization algorithms base their updates solely on the average mini-batch gradient, and it has been shown that tracking additional quantities such…
Neural Spatio-Temporal Point Processes
Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
We propose a new class of parameterizations for spatio-temporal point processes which leverage Neural ODEs as a computational method and enable flexible, high-fidelity models of di…
"Hey, that's not an ODE": Faster ODE Adjoints via Seminorms
Patrick Kidger, Ricky T. Q. Chen, Terry Lyons
Neural differential equations may be trained by backpropagating gradients via the adjoint method, which is another differential equation typically solved using an adaptive-step-siz…
SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models
Yucen Luo, Alex Beatson, Mohammad Norouzi +4
Standard variational lower bounds used to train latent variable models produce biased estimates of most quantities of interest. We introduce an unbiased estimator of the log margin…