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Computer Science

D-Index
33
Citations
18278
World Ranking
12341
National Ranking
4993

Overview

Ben Poole is a researcher affiliated with Google in the United States, with a focus on computer science and related fields. Their work encompasses a range of subfields including computer vision and pattern recognition, artificial intelligence, computer graphics and computer-aided design, statistical and nonlinear physics, and signal processing.

The main themes of Ben Poole's research include generative adversarial networks and image synthesis, computer graphics and visualization techniques, model reduction and neural networks, advanced vision and imaging, machine learning and data classification, 3D shape modeling and analysis, and music and audio processing.

Ben Poole has published extensively, with 37 works in prominent computer vision and pattern recognition venues and numerous contributions to arXiv. Their recent papers include:

  • DreamFusion: Text-to-3D using 2D Diffusion, 2022, arXiv (Cornell University)
  • Imagen Video: High Definition Video Generation with Diffusion Models, 2022, arXiv (Cornell University)
  • Zero-Shot Text-Guided Object Generation with Dream Fields, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Score-Based Generative Modeling through Stochastic Differential Equations, 2020, arXiv (Cornell University)
  • What Makes for Good Views for Contrastive Learning?, 2020, arXiv (Cornell University)

Throughout their research career, Ben Poole has collaborated frequently with other experts in the field. Their most frequent coauthors include Jonathan T. Barron, Ben Mildenhall, Aleksander Holynski, Jascha Sohl-Dickstein, and Diederik P. Kingma, with multiple joint publications reflecting ongoing research partnerships.

Ben Poole's work has been disseminated predominantly through arXiv, with over 30 publications on this platform, alongside contributions to high-profile venues such as the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Neuron.

Their contributions span various advanced topics in computer science and engineering, addressing foundational and applied challenges in generative modeling, 3D reconstruction, machine learning methodologies, and visualization. This multidisciplinary approach aligns with the evolving landscape of artificial intelligence and computer graphics research.

Best Publications

  • Categorical Reparameterization with Gumbel-Softmax

    Eric Jang;Shixiang Gu;Ben Poole

  • Score-Based Generative Modeling through Stochastic Differential Equations

    Yang Song;Jascha Sohl-Dickstein;Diederik P Kingma;Abhishek Kumar

  • Adversarially Learned Inference

    Vincent Dumoulin;Ishmael Belghazi;Ben Poole;Alex Lamb

  • DreamFusion: Text-to-3D using 2D Diffusion

    Unknown

  • Continual Learning Through Synaptic Intelligence.

    Friedemann Zenke;Ben Poole;Surya Ganguli

  • Adversarially Learned Inference

    Vincent Dumoulin;Ishmael Belghazi;Ben Poole;Olivier Mastropietro

  • Imagen Video: High Definition Video Generation with Diffusion Models

    Unknown

  • Unrolled Generative Adversarial Networks

    Luke Metz;Ben Poole;David Pfau;Jascha Sohl-Dickstein

  • What Makes for Good Views for Contrastive Learning

    Yonglong Tian;Chen Sun;Ben Poole;Dilip Krishnan

  • Zero-Shot Text-Guided Object Generation with Dream Fields

    Unknown

  • On the expressive power of deep neural networks

    Maithra Raghu;Ben Poole;Jon M. Kleinberg;Surya Ganguli

  • Exponential expressivity in deep neural networks through transient chaos

    Ben Poole;Subhaneil Lahiri;Maithreyi Raghu;Jascha Sohl-Dickstein

  • On Variational Bounds of Mutual Information

    Ben Poole;Sherjil Ozair;Aaron van den Oord;Alexander A. Alemi

  • The Fast Bilateral Solver

    Jonathan T. Barron;Ben Poole

  • Fixing a Broken ELBO

    Alexander A. Alemi;Ben Poole;Ian Fischer;Joshua V. Dillon

  • Variational Diffusion Models

    Diederik P. Kingma;Tim Salimans;Ben Poole;Jonathan Ho

  • Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation

    Raphael Gontijo Lopes;Dong Yin;Ben Poole;Justin Gilmer

  • Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods

    Jascha Sohl-Dickstein;Ben Poole;Surya Ganguli

  • Weakly-Supervised Disentanglement Without Compromises

    Francesco Locatello;Ben Poole;Gunnar Rätsch;Bernhard Schölkopf

  • Discovering Precise Temporal Patterns in Large-Scale Neural Recordings through Robust and Interpretable Time Warping

    Alex H. Williams;Ben Poole;Niru Maheswaranathan;Ashesh K. Dhawale

  • Categorical Reparametrization with Gumble-Softmax

    Eric Jang;Shixiang Gu;Ben Poole

  • Preventing Posterior Collapse with delta-VAEs

    Ali Razavi;Aäron van den Oord;Ben Poole;Oriol Vinyals

  • Analyzing noise in autoencoders and deep networks

    Ben Poole;Jascha Sohl-Dickstein;Surya Ganguli

  • Weakly-Supervised Disentanglement Without Compromises

    Francesco Locatello;Ben Poole;Gunnar Raetsch;Bernhard Schölkopf

Frequent Co-Authors

Jascha Sohl-Dickstein
Jascha Sohl-Dickstein Google (United States)
Surya Ganguli
Surya Ganguli Stanford University
Aaron van den Oord
Aaron van den Oord Google (United States)
Stephen I. Ryu
Stephen I. Ryu Stanford University
Stefano Ermon
Stefano Ermon Stanford University
Chen Sun
Chen Sun Google (United States)
Jonathan T. Barron
Jonathan T. Barron Google (United States)
Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA
Shixiang Gu
Shixiang Gu Google (United States)

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