Cargando…

Introduction to the industry session

Mostrar otras versiones (5)

Detalles Bibliográficos
Autores principales:	Schramm, Steven Randolph, Haake, Rudiger, Seyfert, Paul, Stoye, Markus, Moneta, Lorenzo
Lenguaje:	eng
Publicado:	2018
Materias:	Machine Learning
Acceso en línea:	http://cds.cern.ch/record/2312413

Ejemplares similares

Welcome
por: Schramm, Steven Randolph, et al.
Publicado: (2018)

Close-out and challenge results
por: Schramm, Steven Randolph, et al.
Publicado: (2018)

Introduction to the workshop
por: Schramm, Steven Randolph, et al.
Publicado: (2017)

Session introduction
por: CERN. Geneva
Publicado: (2017)

Session introduction
por: CERN. Geneva
Publicado: (2017)

Close-out
por: Schramm, Steven Randolph
Publicado: (2017)

Exploring neural networks to improve b-jet tagging with the ALICE detector
por: Haake, Rudiger
Publicado: (2017)

Tutorial: TMVA
por: Moneta, Lorenzo
Publicado: (2018)

Tutorial 1: TMVA
por: Gleyzer, Sergei, et al.
Publicado: (2017)

DeepFlavour in CMS
por: Stoye, Markus
Publicado: (2017)

DeepJet: a deep-learned multiclass jet-tagger for slim and fat jets
por: Gouskos, Loukas, et al.
Publicado: (2018)

Studies to mitigate difference between real data and simulation for jet tagging
por: Buchmuller, Oliver, et al.
Publicado: (2018)

Industry-HEP panel on Machine Learning
por: CERN. Geneva
Publicado: (2017)

Jet reconstruction and heavy jet tagging at LHCb
por: Sestini, Lorenzo
Publicado: (2017)

Robust regression and model compression
por: Ivanov, Marian
Publicado: (2018)

Recent developments in deep-learning applied to open HEP data
por: Strong, Giles Chatham
Publicado: (2018)

ML as a Service for HEP
por: Kuznetsov, Valentin Y
Publicado: (2018)

CWoLa hunting
por: Collins, Jack, et al.
Publicado: (2018)

Guiding New Physics Searches with Unsupervised Learning
por: De Simone, Andrea
Publicado: (2018)

Machine learning as an instrument for data unfolding
por: Glazov, Alexander
Publicado: (2018)

Learning New Physics from a machine
por: Wulzer, Andrea
Publicado: (2018)

Convolutional Neural Network for Track Seed Filtering at the CMS HLT
por: Di Florio, Adriano
Publicado: (2018)

HL-LHC tracking challenge
por: Vlimant, Jean-Roch
Publicado: (2018)

Fast calorimeter simulation in LHCb
por: Zakharov, Egor
Publicado: (2018)

Generative Models for Fast Cluster Simulations in the TPC for the ALICE Experiment
por: Deja, Kamil Rafal
Publicado: (2018)

Machine Learning For Enterprises: Beyond Open Source
por: Puget, Jean-Francois
Publicado: (2018)

Surrogate Models for Fun and Profit
por: Ustyuzhanin, Andrey
Publicado: (2018)

Adversarial Tuning of Perturbative Parameters in Non-Differentiable Physics Simulators
por: Paganini, Michela
Publicado: (2018)

Tutorial: Keras/TensorFlow
por: Wunsch, Stefan
Publicado: (2018)

Joint Wasserstein GAN contribution
por: Glombitza, Jonas, et al.
Publicado: (2018)

DeepJet: a portable ML environment for HEP
por: mehta, swapneel, et al.
Publicado: (2018)

Searching for new physics without knowing the signal model
por: Amoroso, Simone, et al.
Publicado: (2018)

QCD or What?
por: Thompson, Jennifer
Publicado: (2018)

Invited talk: Deep Learning Meets Physics
por: Hochreiter, Sepp
Publicado: (2018)

Invited talk: Overview, RNNs and alike in HEP
por: Cranmer, Kyle Stuart
Publicado: (2018)

Jupyter live demo
por: Forde, Jessica
Publicado: (2018)

Interpreting Deep Neural Networks and their Predictions
por: Samek, Wojciech
Publicado: (2018)

What is the machine learning.
por: Ostdiek, Bryan
Publicado: (2018)

Identifying the relevant dependencies of the neural network response on characteristics of the input space
por: Wunsch, Stefan
Publicado: (2018)

Particle identification at LHCb: new calibration techniques and machine learning classification algorithms
por: Lucio Martinez, Miriam
Publicado: (2018)

Cannot write session to /tmp/vufind_sessions/sess_s06fdk231p1ifbok4enmurc3gm