Kavli Affiliate: Jeffrey B. Neaton | First 5 Authors: Shufeng Kong, Francesco Ricci, Dan Guevarra, Jeffrey B. Neaton, Carla P. Gomes | Summary: Machine learning for materials discovery has largely focused on predicting an individual scalar rather than multiple related properties, where spectral properties are an important example. Fundamental spectral properties include the phonon density […]

Kavli Affiliate: K. Birgitta Whaley | First 5 Authors: Ian Convy, K. Birgitta Whaley, , , | Summary: We consider the problem of continuous quantum error correction from a Bayesian perspective, proposing a pair of digital filters using logarithmic probabilities that are able to achieve near-optimal performance on a three-qubit bit-flip code while still being […]

Kavli Affiliate: K. Birgitta Whaley | First 5 Authors: Ian Convy, Haoran Liao, Song Zhang, Sahil Patel, William P. Livingston | Summary: We propose a machine learning algorithm for continuous quantum error correction that is based on the use of a recurrent neural network to identity bit-flip errors from continuous noisy syndrome measurements. The algorithm […]

Kavli Affiliate: K. Birgitta Whaley | First 5 Authors: Zeng-Zhao Li, Liwen Ko, Zhibo Yang, Mohan Sarovar, K. Birgitta Whaley | Summary: We study the interplay between two environmental influences on excited state energy transfer in photosynthetic light harvesting complexes, namely, vibrationally assisted energy transfer(VAET) and environment-assisted quantum transport (ENAQT), considering a dimeric chromophore donor-acceptor […]

Kavli Affiliate: Feng Wang | First 5 Authors: Feng Wang, Tao Kong, Rufeng Zhang, Huaping Liu, Hang Li | Summary: We present TWIST, a simple and theoretically explainable self-supervised representation learning method by classifying large-scale unlabeled datasets in an end-to-end way. We employ a siamese network terminated by a softmax operation to produce twin class […]

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik, | Summary: In many domains, including healthcare, biology, and climate science, time series are irregularly sampled with varying time intervals between successive readouts and different subsets of variables (sensors) observed at different time points. Here, we introduce RAINDROP, a […]

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, , , , | Summary: Inferring the underlying graph topology that characterizes structured data is pivotal to many graph-based models when pre-defined graphs are not available. This paper focuses on learning graphs in the case of sequential data in dynamic environments. For sequential data, we […]

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Qiao Wang, , , | Summary: This paper endeavors to learn time-varying graphs by using structured temporal priors that assume underlying relations between arbitrary two graphs in the graph sequence. Different from many existing chain structure based methods in which the priors like temporal homogeneity […]

Kavli Affiliate: Joel E. Moore | First 5 Authors: Maxime Dupont, Joel E. Moore, , , | Summary: Quantum criticality emerges from the collective behavior of many interacting quantum particles, often at the transition between different phases of matter. It is one of the cornerstones of condensed matter physics, which we access on noisy intermediate-scale […]

Kavli Affiliate: Xiang Zhang | First 5 Authors: Yihang Yin, Qingzhong Wang, Siyu Huang, Haoyi Xiong, Xiang Zhang | Summary: Contrastive learning has been widely applied to graph representation learning, where the view generators play a vital role in generating effective contrastive samples. Most of the existing contrastive learning methods employ pre-defined view generation methods, […]