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Dirichlet Gaussian published presentations and documents on DocSlides.

1 Atmospheric models for damage costs

1 Atmospheric models for damage costs

  • myesha-ticknor
  • 25 Slides

. TRADD, part 2. Ari Rabl, ARMINES/. Ecole. des...

יסודות אופטיקה ופוטוניקה ביו-רפ

יסודות אופטיקה ופוטוניקה ביו-רפ

  • natalia-silvester
  • 65 Slides

Fundamentals of biomedical optics and photonics. ...

Tutorial

Tutorial

  • lindy-dunigan
  • 74 Slides

on. Bayesian. . Techniques. for. . Inference. A...

Dynamic Floating-Point Cancellation Detection

Dynamic Floating-Point Cancellation Detection

  • natalia-silvester
  • 32 Slides

Michael O. Lam (Presenter). Jeffrey K. Hollingswo...

Unsupervised learning

Unsupervised learning

  • ellena-manuel
  • 47 Slides

David Kauchak. CS 451 – Fall 2013. Administrati...

Clustering Beyond

Clustering Beyond

  • lindy-dunigan
  • 41 Slides

K. -means. David Kauchak. CS 451 – Fall 2013. A...

Sampling from Gaussian Graphical Models via Spectral Sparsi

Sampling from Gaussian Graphical Models via Spectral Sparsi

  • briana-ranney
  • 40 Slides

Richard Peng. M.I.T.. Joint work with . Dehua. C...

MDL Many of the figures are provided by Chris Bishop

MDL Many of the figures are provided by Chris Bishop

  • tawny-fly
  • 45 Slides

from his textbook: ”Pattern Recognition and Mac...

Measurement

Measurement

  • luanne-stotts
  • 12 Slides

R. epeatability. WFC3 – spatial . s. can mode a...

Spatial Preprocessing

Spatial Preprocessing

  • giovanna-bartolotta
  • 41 Slides

Ged Ridgway, FMRIB/FIL. With thanks to John Ashbu...

Towards Privacy-Sensitive Participatory Sensing

Towards Privacy-Sensitive Participatory Sensing

  • mitsue-stanley
  • 24 Slides

K.L. Huang, S. S. . Kanhere. and W. . Hu. Presen...

Accelerating Spatially Varying Gaussian Filters

Accelerating Spatially Varying Gaussian Filters

  • tatyana-admore
  • 53 Slides

Jongmin Baek and David E. Jacobs. Stanford Univer...

A Review of Bell-Shaped Curves

A Review of Bell-Shaped Curves

  • stefany-barnette
  • 16 Slides

David M. Harrison, Dept. of Physics, Univ. of Tor...

The Little Big Data Showdown

The Little Big Data Showdown

  • conchita-marotz
  • 15 Slides

ECE 8110 Pattern Recognition and Machine Learning...

SIFT &

SIFT &

  • trish-goza
  • 43 Slides

MatLab. Pier Luigi . Mazzeo. Sift purpose. Find a...

SLAM Accelerated

SLAM Accelerated

  • trish-goza
  • 36 Slides

Using Hardware to improve SLAM algorithm performa...

A simple smoothed seismicity forecast for prospective testi

A simple smoothed seismicity forecast for prospective testi

  • liane-varnes
  • 22 Slides

Jeremy Douglas Zechar. Lamont-Doherty Earth Obser...

S tochastic processes

S tochastic processes

  • yoshiko-marsland
  • 63 Slides

Lecture. 7. Linear time invariant systems. 1. Ra...

Parte 4

Parte 4

  • lois-ondreau
  • 27 Slides

Peer. Review. Section . 6. Download at: http://w...

Wavepackets

Wavepackets

  • yoshiko-marsland
  • 27 Slides

. Outline. Review: Reflection & Refraction...

Supervised Learning Recap

Supervised Learning Recap

  • test
  • 40 Slides

Machine Learning. Last Time. Support Vector Machi...

Principled

Principled

  • olivia-moreira
  • 20 Slides

Approximations in Probabilistic Programming. The ...

Accurate Translucent Material Rendering under Spherical Gau

Accurate Translucent Material Rendering under Spherical Gau

  • faustina-dinatale
  • 36 Slides

Ling-Qi Yan. 1. , . Yahan. Zhou. 2. , Kun Xu. 1....

Experimental Uncertainties:

Experimental Uncertainties:

  • danika-pritchard
  • 24 Slides

A Practical Guide. What you should already know w...

INTRODUCTION

INTRODUCTION

  • faustina-dinatale
  • 35 Slides

TO. . Machine . Learning. 3rd Edition. ETHEM . A...

Seminar using

Seminar using

  • cheryl-pisano
  • 17 Slides

Unsolved Problems in Number Theory. Robert Styer....

Computational

Computational

  • conchita-marotz
  • 54 Slides

Photography:. Sampling + . Reconstruction. ...

Computational Photography

Computational Photography

  • liane-varnes
  • 92 Slides

L. ecture 3 . – filtering and frequencies. CS ....

Classification of place

Classification of place

  • liane-varnes
  • 19 Slides

of articulation . in . unvoiced stops . with . sp...

CS5540: Computational Techniques for Analyzing Clinical Dat

CS5540: Computational Techniques for Analyzing Clinical Dat

  • debby-jeon
  • 67 Slides

Lecture 7:. . Statistical Estimation: Least Squa...

Topic models

Topic models

  • sherrill-nordquist
  • 70 Slides

Source: “Topic models”, David . Blei. , MLS...

Larvae are not

Larvae are not

  • pasty-toler
  • 1 Slides

Lagrangian. !. Theoretical work indicates that an...

Morphing

Morphing

  • alexa-scheidler
  • 27 Slides

WU PO-HUNG. Morphing. http://www.youtube.com/watc...

A Tour of

A Tour of

  • luanne-stotts
  • 87 Slides

Image . Denoising. Shahar . Kovalsky. Alon. . Fa...

Beating CountSketch for Heavy Hitters in Insertion Streams

Beating CountSketch for Heavy Hitters in Insertion Streams

  • danika-pritchard
  • 18 Slides

Vladimir . Braverman. . (JHU). Stephen R. . Che...

SIFT

SIFT

  • pamella-moone
  • 47 Slides

keypoint. detection. D. Lowe, . Distinctive . im...

Hawkes Learning Systems

Hawkes Learning Systems

  • conchita-marotz
  • 28 Slides

College Algebra. Section 8.2: . Matrix Notation a...

Statistical Topic Modeling

Statistical Topic Modeling

  • calandra-battersby
  • 23 Slides

part 1. Andrea Tagarelli. Univ. of Calabria, Ital...

Anomaly detection

Anomaly detection

  • myesha-ticknor
  • 49 Slides

Problem motivation. Machine Learning. Anomaly det...

Deblurring with a scale-space approach

Deblurring with a scale-space approach

  • mitsue-stanley
  • 24 Slides

Gaussian degradation occurs in a large number of ...

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