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Highly Cited

2016

Highly Cited

2016

Deep learning tools have gained tremendous attention in applied machine learning. However such tools for regression and… Expand

Highly Cited

2015

Highly Cited

2015

Inspired by recent work in machine translation and object detection, we introduce an attention based model that automatically… Expand

Highly Cited

2014

Highly Cited

2014

Abstract: How can we perform efficient inference and learning in directed probabilistic models, in the presence of continuous… Expand

Highly Cited

2003

Highly Cited

2003

We propose a generative model for text and other collections of discrete data that generalizes or improves on several previous… Expand

Highly Cited

2003

Highly Cited

2003

Many problems in information processing involve some form of dimensionality reduction. In this paper, we introduce Locality… Expand

Highly Cited

2003

Highly Cited

2003

Newton Methods for Nonsmooth Equations.- Global Methods for Nonsmooth Equations.- Equation-Based Algorithms for Complementarity… Expand

Highly Cited

1986

Highly Cited

1986

I. Mathematical Foundation of the Stokes Problem.- 1. Generalities on Some Elliptic Boundary Value Problems.- 1.1. Basic Concepts… Expand

Highly Cited

1981

Highly Cited

1981

The time-dependent variational principle (TDVP).- Lie algebras and symplectic structures.- Symplectic structure on group… Expand

Highly Cited

1979

Highly Cited

1979

It is frequently explicitly or implicitly assumed that if a variational principle is invariant under some symmetry groupG, then… Expand

Highly Cited

1974

Highly Cited

1974

The variational principle states that if a differentiable functional F attains its minimum at some point zi, then F’(C) = 0; it… Expand