Magnetic State Generation using Hamiltonian Guided Variational Autoencoder with Spin Structure Stabilization
نویسندگان
چکیده
منابع مشابه
Syntax-Directed Variational Autoencoder for Molecule Generation
Deep generative models have been enjoying success in modeling continuous data. However it remains challenging to capture the representations for discrete structures with formal grammars and semantics. How to generate both syntactically and semantically correct data still remains largely an open problem. Inspired by the theory of compiler where syntax and semantics check is done via syntax-direc...
متن کاملMusic generation with variational recurrent autoencoder supported by history
A serious problem for automated music generation is to propose the model that could reproduce complex temporal and melodic patterns that would correspond to the style of the training input. We propose a new architecture of an artificial neural network that helps to deal with such tasks. We discuss the proposed approach and compare it with a long short-term memory language model and with variati...
متن کاملA Classifying Variational Autoencoder with Application to Polyphonic Music Generation
The variational autoencoder (VAE) is a popular probabilistic generative model. However, one shortcoming of VAEs is that the latent variables cannot be discrete, which makes it difficult to generate data from different modes of a distribution. Here, we propose an extension of the VAE framework that incorporates a classifier to infer the discrete class of the modeled data. To model sequential dat...
متن کاملA Hybrid Convolutional Variational Autoencoder for Text Generation
In this paper we explore the effect of architectural choices on learning a variational autoencoder (VAE) for text generation. In contrast to the previously introduced VAE model for text where both the encoder and decoder are RNNs, we propose a novel hybrid architecture that blends fully feed-forward convolutional and deconvolutional components with a recurrent language model. Our architecture e...
متن کاملVariational Lossy Autoencoder
Representation learning seeks to expose certain aspects of observed data in a learned representation that’s amenable to downstream tasks like classification. For instance, a good representation for 2D images might be one that describes only global structure and discards information about detailed texture. In this paper, we present a simple but principled method to learn such global representati...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Advanced Science
سال: 2021
ISSN: 2198-3844,2198-3844
DOI: 10.1002/advs.202004795