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Traditional databases commonly support efficient query and update procedures that operate in time which is sublinear in the size of the database. Our goal in this paper is to take a first step toward dynamic reasoning in probabilistic…

Artificial Intelligence · Computer Science 2009-09-25 A. L. Delcher , A. J. Grove , S. Kasif , J. Pearl

Neural language models are usually trained to match the distributional properties of a large-scale corpus by minimizing the log loss. While straightforward to optimize, this approach forces the model to reproduce all variations in the…

Computation and Language · Computer Science 2020-05-04 Daniel Kang , Tatsunori Hashimoto

A recently discovered universal rank-based matrix method to extract trends from noisy time series is described in [1] but the formula for the output matrix elements, implemented there as an open-access supplement MATLAB computer code, is…

Data Analysis, Statistics and Probability · Physics 2020-06-24 D. J. Kestner , G. R. Ierley , A. B. Kostinski

Large language models suffer from "hallucinations"-logical inconsistencies induced by semantic noise. We propose that current architectures operate in a "Metric Phase," where causal order is vulnerable to spontaneous symmetry breaking.…

Machine Learning · Computer Science 2026-01-09 Ilmo Sung

Narrowband power line communication (NB-PLC) systems are an attractive solution for supporting current and future smart grids. A technology proposed to enhance data rate in NB-PLC is multiple-input multiple-output (MIMO) transmission over…

We present a novel prompt design for Large Language Models (LLMs) tailored to Asynchronous Time Series. Unlike regular time series, which assume values at evenly spaced time points, asynchronous time series consist of timestamped events…

Machine Learning · Computer Science 2025-02-05 Shubham Gupta , Thibaut Durand , Graham Taylor , Lilian W. Białokozowicz

Quantum supremacy poses that a realistic quantum computer can perform a calculation that classical computers cannot in any reasonable amount of time. It has become a topic of significant research interest since the birth of the field, and…

Quantum Physics · Physics 2023-01-10 Kabgyun Jeong

A basic feasible probabilistic purification of unknown noisy coherent states, outgoing from different state preparations with unknown mean number of thermal photons, is proposed. The scheme is based only on a linear-optical network with an…

Quantum Physics · Physics 2007-06-14 Petr Marek , Radim Filip

The usual representation of quantum algorithms is limited to the process of solving the problem. We extend it to the process of setting the problem. Bob, the problem setter, selects a problem-setting by the initial measurement. Alice, the…

Quantum Physics · Physics 2019-10-23 Giuseppe Castagnoli , Eliahu Cohen , Artur Ekert , Avshalom Elitzur

A non trace-preserving map describing a probabilistic but heralded noiseless linear amplifier has recently been proposed and experimentally demonstrated. Here, we exhibit another remarkable feature of this peculiar transformation, namely…

Quantum Physics · Physics 2013-01-29 C. N. Gagatsos , E. Karpov , N. J. Cerf

It is argued that our universe happens to be in a state of statistical equilibrium at the hidden-variable level, such that nonlocality is masked by quantum noise. To account for this 'quantum equilibrium', we outline a subquantum…

Quantum Physics · Physics 2007-05-23 Antony Valentini

Time series classification with missing data is a prevalent issue in time series analysis, as temporal data often contain missing values in practical applications. The traditional two-stage approach, which handles imputation and…

Machine Learning · Computer Science 2024-08-13 Pengshuai Yao , Mengna Liu , Xu Cheng , Fan Shi , Huan Li , Xiufeng Liu , Shengyong Chen

Parameter estimation is of fundamental importance in areas from atomic spectroscopy and atomic clocks to gravitational wave detection. Entangled probes provide a significant precision gain over classical strategies in the absence of noise.…

Quantum Physics · Physics 2013-10-28 R. Chaves , J. B. Brask , M. Markiewicz , J. Kolodynski , A. Acin

Although the emergence of a fully-functional quantum computer may still be far away from today, in the near future, it is possible to have medium-size, special-purpose, quantum devices that can perform computational tasks not efficiently…

Quantum Physics · Physics 2017-06-28 Man-Hong Yung , Xun Gao

Current experiments are taking the first steps toward noise-resilient logical qubits. Crucially, a quantum computer must not merely store information, but also process it. A fault-tolerant computational procedure ensures that errors do not…

Quantum Physics · Physics 2018-11-13 Earl T. Campbell , Barbara M. Terhal , Christophe Vuillot

A method for simulating power law noise in clocks and oscillators is presented based on modification of the spectrum of white phase noise, then Fourier transforming to the time domain. Symmetric real matrices are introduced whose…

Data Analysis, Statistics and Probability · Physics 2011-03-28 Neil Ashby

Synchronization is shown to occur in spatially extended systems under the effect of additive spatio-temporal noise. In analogy to low dimensional systems, synchronized states are observable only if the maximum Lyapunov exponent $\Lambda$ is…

chao-dyn · Physics 2016-11-23 L. Baroni , R. Livi , A. Torcini

Quantum computers now show the promise of surpassing any possible classical machine. However, errors limit this ability and current machines do not have the ability to implement error correcting codes due to the limited number of qubits and…

Quantum Physics · Physics 2023-09-26 Zhao-Ming Wang , Feng-Hua Ren , Mark S. Byrd , Lian-Ao Wu

Demonstrating quantum supremacy, a complexity-guaranteed quantum advantage against over the best classical algorithms by using less universal quantum devices, is an important near-term milestone for quantum information processing. Here we…

Quantum Physics · Physics 2016-10-13 Keisuke Fujii

Our goal is to $\textit{efficiently}$ discover a compact set of temporal logic rules to explain irregular events of interest. We introduce a neural-symbolic rule induction framework within the temporal point process model. The negative…

Machine Learning · Computer Science 2024-06-07 Yang Yang , Chao Yang , Boyang Li , Yinghao Fu , Shuang Li
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