223 citations · 526 across the 7 of their papers we have counts for
7 papers
Variational Benchmarks for Quantum Many-Body Problems
Dian Wu, Riccardo Rossi, Filippo Vicentini +30
The continued development of computational approaches to many-body ground-state problems in physics and chemistry calls for a consistent way to assess its overall progress. In this…
From Tensor Network Quantum States to Tensorial Recurrent Neural Networks
Dian Wu, Riccardo Rossi, Filippo Vicentini +1
We show that any matrix product state (MPS) can be exactly represented by a recurrent neural network (RNN) with a linear memory update. We generalize this RNN architecture to 2D la…
NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems
Filippo Vicentini, Damian Hofmann, Attila Szabó +8
We introduce version 3 of NetKet, the machine learning toolbox for many-body quantum physics. NetKet is built around neural-network quantum states and provides efficient algorithms…
Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks
Dian Wu, Riccardo Rossi, Giuseppe Carleo
Efficient sampling of complex high-dimensional probability distributions is a central task in computational science. Machine learning methods like autoregressive neural networks, u…
RG-Flow: A hierarchical and explainable flow model based on renormalization group and sparse prior
Hong-Ye Hu, Dian Wu, Yi-Zhuang You +2
Flow-based generative models have become an important class of unsupervised learning approaches. In this work, we incorporate the key ideas of renormalization group (RG) and sparse…
Influenza Modeling Based on Massive Feature Engineering and International Flow Deconvolution
Ziming Liu, Yixuan Wang, Zizhao Han +1
In this article, we focus on the analysis of the potential factors driving the spread of influenza, and possible policies to mitigate the adverse effects of the disease. To be prec…
Solving Statistical Mechanics Using Variational Autoregressive Networks
Dian Wu, Lei Wang, Pan Zhang
We propose a general framework for solving statistical mechanics of systems with finite size. The approach extends the celebrated variational mean-field approaches using autoregres…