3.7k citations · 13.3k across the 162 of their papers we have counts for
14 papers · 1 filter
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models
Xingyu Xie, Pan Zhou, Huan Li +2
In deep learning, different kinds of deep networks typically need different optimizers, which have to be chosen after multiple trials, making the training process inefficient. To r…
Universal Antisymmetry in Fermionic Neural Networks
Tianyu Pang, Shuicheng Yan, Min Lin
Fermionic neural network (FermiNet) is a recently proposed wavefunction Ansatz, which is used in variational Monte Carlo (VMC) methods to solve the many-electron Schrödinger equati…
Value-Consistent Representation Learning for Data-Efficient Reinforcement Learning
Yang Yue, Bingyi Kang, Zhongwen Xu +2
Deep reinforcement learning (RL) algorithms suffer severe performance degradation when the interaction data is scarce, which limits their real-world application. Recently, visual r…
Towards Understanding Why Mask-Reconstruction Pretraining Helps in Downstream Tasks
Jiachun Pan, Pan Zhou, Shuicheng Yan
For unsupervised pretraining, mask-reconstruction pretraining (MRP) approaches, e.g. MAE and data2vec, randomly mask input patches and then reconstruct the pixels or semantic featu…
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
Tianyu Pang, Min Lin, Xiao Yang +2
The trade-off between robustness and accuracy has been widely studied in the adversarial literature. Although still controversial, the prevailing view is that this trade-off is inh…
Dual-constrained Deep Semi-Supervised Coupled Factorization Network with Enriched Prior
Yan Zhang, Zhao Zhang, Yang Wang +4
Nonnegative matrix factorization is usually powerful for learning the "shallow" parts-based representation, but it clearly fails to discover deep hierarchical information within bo…