Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo

2 code implementations • 17 Jul 2023 • Ruichen Li, Haotian Ye, Du Jiang, Xuelan Wen, Chuwei Wang, Zhe Li, Xiang Li, Di He, Ji Chen, Weiluo Ren, LiWei Wang

Neural network-based variational Monte Carlo (NN-VMC) has emerged as a promising cutting-edge technique of ab initio quantum chemistry.

Efficient Neural Network Variational Monte Carlo

Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective

1 code implementation • 4 Oct 2022 • Bohang Zhang, Du Jiang, Di He, LiWei Wang

Designing neural networks with bounded Lipschitz constant is a promising way to obtain certifiably robust classifiers against adversarial examples.

Robust classification

Boosting the Certified Robustness of L-infinity Distance Nets

2 code implementations • ICLR 2022 • Bohang Zhang, Du Jiang, Di He, LiWei Wang

Recently, Zhang et al. (2021) developed a new neural network architecture based on $\ell_\infty$-distance functions, which naturally possesses certified $\ell_\infty$ robustness by its construction.