activity
20042019
most citedLingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

184 citations · 421 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2019★ 184 cited

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

Jonathan Shen, Patrick Nguyen, Yonghui Wu +88

Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models a…

stat.ML2017★ 1 cited

Lattice Rescoring Strategies for Long Short Term Memory Language Models in Speech Recognition

Shankar Kumar, Michael Nirschl, Daniel Holtmann-Rice +3

Recurrent neural network (RNN) language models (LMs) and Long Short Term Memory (LSTM) LMs, a variant of RNN LMs, have been shown to outperform traditional N-gram LMs on speech rec…

hep-th2017

Superconformal Symmetry and Correlation Functions

Michael Nirschl

The N = 2, 4 superconformal symmetry constraints in d = 4 for four point functions of chiral primary 1/2-BPS operators are derived. The operators are described by symmetric tracele…

hep-th2006★ 63 cited

Conjectures for Large N Superconformal N=4 Chiral Primary Four Point Functions

F. A. Dolan, M. Nirschl, H. Osborn

An expression for the four point function for half-BPS operators belonging to the [0,p,0] SU(4) representation in N=4 superconformal theories at strong coupling in the large N limi…

hep-th2004★ 173 cited

Superconformal Ward Identities and their Solution

M. Nirschl, H. Osborn

Superconformal Ward identities are derived for the the four point functions of chiral primary BPS operators for superconformal symmetry in four dimensions. Manipulations o…