Andreas Christian Müller Curriculum Vitae Address: 156 East 2nd Street, New York, NY Phone: +Email:

Source URL: amueller.github.io

• Machine learning
• Artificial intelligence
• Cognitive science
• Cybernetics
• Artificial neural networks
• Free statistical software
• Deep learning
• Computational neuroscience
• Conditional random field
• Scikit-learn
• Boltzmann machine

NCSU_SAS_SAM: Deep Encoding and Reconstruction for Normalization of Noisy Text Samuel P. Leeman-Munk James C. Lester Center for Educational Informatics North Carolina State University

Source URL: noisy-text.github.io

• Artificial neural networks
• Cybernetics
• Applied mathematics
• Artificial intelligence
• Deep learning
• Convolutional neural network
• Feature learning
• Backpropagation
• Autoencoder
• Artificial neuron
• Feedforward neural network

How to Publish HITs on Amazon Mechanical Turk Jianxiong Xiao Abstract: This is a practical introduction to teach how to use Amazon Mechanical Turk, using the diversity experiments in my NIPS 2013 paper "Learning Deep Fea

Source URL: vision.princeton.edu

• Software
• Computing
• Application software
• HTML
• Comma-separated values
• Amazon Mechanical Turk
• HTML element
• MATLAB
• Tab key
• Framing
• CSV application support

Mark  D.  Hill,  UW-­‐‑Madison • IT ecosystem has benefited o 1000x performance gainso 1000x distributed/multicore/coreso W/ 1 MIPS: no deep learning or Siri

Source URL: cra.org

Deep-Sea Research I}294 A comparison of the quantity and composition of material caught in a neutrally buoyant versus surface-tethered sediment trap Ken O. Buesseler!,*, Deborah K. Steinberg",

Source URL: cafethorium.whoi.edu

• Sediment trap
• Trap
• UX
• Learning

Deep Blue Kids Director’s Manual Deep Blue Coordinator’s Guidebook Introduction Welcome to the Coordinator’s Guidebook. You

Source URL: www.deepbluekids.com

• Education
• Learning
• Euthenics
• Educational psychology
• Spirituality
• Pedagogy
• Teaching
• Prayer
• Spiritual practice
• Teacher
• Classroom
• Educational technology

Supplementary for Structural-RNN: Deep Learning on Spatio-Temporal Graphs Ashesh Jain1,2 , Amir R. Zamir1 , Silvio Savarese1 , and Ashutosh Saxena3 Stanford University1 , Cornell University2 , Brain Of Things Inc.3 {ashe

Source URL: cvgl.stanford.edu

• Artificial neural networks
• Computational neuroscience
• Academia
• Deep learning
• Long short-term memory
• Mathematical logic
• Science and technology
• Applied mathematics
• Algorithm
• Motion
• Artificial intelligence

In Proceedings of 37th German Conference on Artificial Intelligence (KI), pp, Springer LNCS 8736, Stuttgart, SeptemberFast Semantic Segmentation of RGB-D Scenes with GPU-Accelerated Deep Neural Networks Nic

Source URL: www.ais.uni-bonn.de

• Computational neuroscience
• Artificial neural networks
• Image processing
• Applied mathematics
• Cybernetics
• Computer vision
• Convolutional neural network
• Deep learning
• Neuroscience
• Artificial intelligence
• Image segmentation

Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems Tsung-Hsien Wen, Milica Gaˇsi´c, Nikola Mrkˇsi´c, Pei-Hao Su, David Vandyke and Steve Young Cambridge University Engineering

Source URL: www.emnlp2015.org

• Artificial neural networks
• Artificial intelligence
• Machine learning
• Computational neuroscience
• Academia
• Deep learning
• Long short-term memory
• Recurrent neural network
• Sepp Hochreiter
• Vanishing gradient problem
• Speech recognition
• Handwriting recognition

Technology Insight: Data Analytics and Machine Learning Pradeep K Dubey – Intel Fellow, Intel Corporation SPCS008 1

Source URL: software.intel.com

• Technology
• Learning
• Machine learning
• Business
• Deep learning
• Intel
• Manufacturing