86 citations · 333 across the 21 of their papers we have counts for
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cs.LG2023★ 1 cited
Convergence of variational Monte Carlo simulation and scale-invariant pre-training
Nilin Abrahamsen, Zhiyan Ding, Gil Goldshlager +1
We provide theoretical convergence bounds for the variational Monte Carlo (VMC) method as applied to optimize neural network wave functions for the electronic structure problem. We…
cs.LG2021★ 2 cited
On the Global Convergence of Gradient Descent for multi-layer ResNets in the mean-field regime
Zhiyan Ding, Shi Chen, Qin Li +1
Finding the optimal configuration of parameters in ResNet is a nonconvex minimization problem, but first-order methods nevertheless find the global optimum in the overparameterized…
cs.LG2021
Overparameterization of deep ResNet: zero loss and mean-field analysis
Zhiyan Ding, Shi Chen, Qin Li +1
Finding parameters in a deep neural network (NN) that fit training data is a nonconvex optimization problem, but a basic first-order optimization method (gradient descent) finds a…