104 research outputs found
Using Multi-Sense Vector Embeddings for Reverse Dictionaries
Popular word embedding methods such as word2vec and GloVe assign a single vector representation to each word, even if a word has multiple distinct meanings. Multi-sense embeddings instead provide different vectors for each sense of a word. However, they typically cannot serve as a drop-in replacement for conventional single-sense embeddings, because the correct sense vector needs to be selected for each word. In this work, we study the effect of multi-sense embeddings on the task of reverse dictionaries. We propose a technique to easily integrate them into an existing neural network architecture using an attention mechanism. Our experiments demonstrate that large improvements can be obtained when employing multi-sense embeddings both in the input sequence as well as for the target representation. An analysis of the sense distributions and of the learned attention is provided as well
A Formal Proof of the Expressiveness of Deep Learning
International audienceDeep learning has had a profound impact on computer science in recent years, with applications to image recognition, language processing, bioinformatics, and more. Recently , Cohen et al. provided theoretical evidence for the superiority of deep learning over shallow learning. We formalized their mathematical proof using Isabelle/HOL. The Isabelle development simplifies and generalizes the original proof, while working around the limitations of the HOL type system. To support the formalization, we developed reusable libraries of formalized mathematics, including results about the matrix rank, the Borel measure, and multivariate polynomials as well as a library for tensor analysis
Numerical study of scars in a chaotic billiard
We study numerically the scaling properties of scars in stadium billiard.
Using the semiclassical criterion, we have searched systematically the scars of
the same type through a very wide range, from ground state to as high as the 1
millionth state. We have analyzed the integrated probability density along the
periodic orbit. The numerical results confirm that the average intensity of
certain types of scars is independent of rather than scales with
. Our findings confirm the theoretical predictions of Robnik
(1989).Comment: 7 pages in Revtex 3.1, 5 PS figures available upon request. To appear
in Phys. Rev. E, Vol. 55, No. 5, 199
Wigner function quantum molecular dynamics
Classical molecular dynamics (MD) is a well established and powerful tool in
various fields of science, e.g. chemistry, plasma physics, cluster physics and
condensed matter physics. Objects of investigation are few-body systems and
many-body systems as well. The broadness and level of sophistication of this
technique is documented in many monographs and reviews, see for example
\cite{Allan,Frenkel,mdhere}. Here we discuss the extension of MD to quantum
systems (QMD). There have been many attempts in this direction which differ
from one another, depending on the type of system under consideration. One
direction of QMD has been developed for condensed matter systems and will not
discussed here, e.g. \cite{fermid}. In this chapter we are dealing with unbound
electrons as they occur in gases, fluids or plasmas. Here, one strategy is to
replace classical point particles by wave packets, e.g.
\cite{fermid,KTR94,zwicknagel06} which is quite successful. At the same time,
this method struggles with problems related to the dispersion of such a packet
and difficulties to properly describe strong electron-ion interaction and bound
state formation. We, therefore, avoid such restrictions and consider a
completely general alternative approach. We start discussion of quantum
dynamics from a general consideration of quantum distribution functions.Comment: 18 pages, based on lecture at Hareaus school on computational phyics,
Greifswald, September 200
Nodal domains statistics - a criterion for quantum chaos
We consider the distribution of the (properly normalized) numbers of nodal
domains of wave functions in 2- quantum billiards. We show that these
distributions distinguish clearly between systems with integrable (separable)
or chaotic underlying classical dynamics, and for each case the limiting
distribution is universal (system independent). Thus, a new criterion for
quantum chaos is provided by the statistics of the wave functions, which
complements the well established criterion based on spectral statistics.Comment: 4 pages, 5 figures, revte
Quasi-classical Molecular Dynamics Simulations of the Electron Gas: Dynamic properties
Results of quasi-classical molecular dynamics simulations of the quantum
electron gas are reported. Quantum effects corresponding to the Pauli and the
Heisenberg principle are modeled by an effective momentum-dependent
Hamiltonian. The velocity autocorrelation functions and the dynamic structure
factors have been computed. A comparison with theoretical predictions was
performed.Comment: 8 figure
Temporal Feedback for Tweet Search with Non-Parametric Density Estimation
This paper investigates the temporal cluster hypothesis: in search tasks where time plays an important role, do relevant documents tend to cluster together in time? We explore this question in the context of tweet search and temporal feedback: starting with an initial set of results from a baseline retrieval model, we estimate the temporal density of relevant documents, which is then used for result reranking. Our contributions lie in a method to characterize this temporal density function using kernel density estimation, with and without human relevance judgments, and an approach to integrating this information into a standard retrieval model. Experiments on TREC datasets confirm that our temporal feedback formulation improves search effectiveness, thus providing support for our hypothesis. Our approach outperforms both a standard baseline and previous temporal retrieval models. Temporal feedback improves over standard lexical feedback (with and without human judgments), illustrating that temporal relevance signals exist independently of document content
Characterization of Quantum Chaos by the Autocorrelation Function of Spectral Determinants
The autocorrelation function of spectral determinants is proposed as a
convenient tool for the characterization of spectral statistics in general, and
for the study of the intimate link between quantum chaos and random matrix
theory, in particular. For this purpose, the correlation functions of spectral
determinants are evaluated for various random matrix ensembles, and are
compared with the corresponding semiclassical expressions. The method is
demonstrated by applying it to the spectra of the quantized Sinai billiards in
two and three dimensions.Comment: LaTeX, 32 pages, 6 figure
Theories for multiple resonances
Two microscopic theories for multiple resonances in nuclei are compared,
n-particle-hole RPA and quantized Time-Dependent Hartree-Fock (TDHF). The
Lipkin-Meshkov-Glick model is used as test case. We find that quantized TDHF is
superior in many respects, except for very small systems.Comment: 14 Pages, 3 figures available upon request
Critical Enhancement of the In-medium Nucleon-Nucleon Cross Section at low Temperatures
The in-medium nucleon-nucleon cross section is calculated starting from the
thermodynamic T-matrix at finite temperatures. The corresponding
Bethe-Salpeter-equation is solved using a separable representation of the Paris
nucleon-nucleon-potential. The energy-dependent in-medium N-N cross section at
a given density shows a strong temperature dependence. Especially at low
temperatures and low total momenta, the in-medium cross section is strongly
modified by in-medium effects. In particular, with decreasing temperature an
enhancement near the Fermi energy is observed. This enhancement can be
discussed as a precursor of the superfluid phase transition in nuclear matter.Comment: 10 pages with 4 figures (available on request from the authors),
MPG-VT-UR 34/94 accepted for publication in Phys. Rev.
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