Next
Livestream will start soon!
Livestream has already ended.
Presentation has not been recorded yet!
  • title: SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification
      0:00 / 0:00
      • Report Issue
      • Settings
      • Playlists
      • Bookmarks
      • Subtitles Off
      • Playback rate
      • Quality
      • Settings
      • Debug information
      • Server sl-yoda-v3-stream-015-alpha.b-cdn.net
      • Subtitles size Medium
      • Bookmarks
      • Server
      • sl-yoda-v3-stream-015-alpha.b-cdn.net
      • sl-yoda-v3-stream-015-beta.b-cdn.net
      • 1963568160.rsc.cdn77.org
      • 1940033649.rsc.cdn77.org
      • Subtitles
      • Off
      • en
      • Playback rate
      • Quality
      • Subtitles size
      • Large
      • Medium
      • Small
      • Mode
      • Video Slideshow
      • Audio Slideshow
      • Slideshow
      • Video
      My playlists
        Bookmarks
          00:00:00
            SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification
            • Settings
            • Sync diff
            • Quality
            • Settings
            • Server
            • Quality
            • Server

            SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification

            Jul 12, 2020

            Speakers

            TG

            Tomer Golany

            Speaker · 0 followers

            KR

            Kira Radinsky

            Speaker · 0 followers

            DF

            Daniel Freedman

            Speaker · 0 followers

            About

            Generating training examples for supervised tasks is a long sought after goal in AI. We study the problem of heart signal electrocardiogram (ECG) synthesis for improved heartbeat classification. ECG synthesis is challenging: the generation of training examples for such biological-physiological systems is not straightforward, due to their dynamic nature in which the various parts of the system interact in complex ways. However, an understanding of these dynamics has been developed for years in th…

            Organizer

            I2
            I2

            ICML 2020

            Account · 2.6k followers

            Categories

            AI & Data Science

            Category · 10.8k presentations

            About ICML 2020

            The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

            Like the format? Trust SlidesLive to capture your next event!

            Professional recording and live streaming, delivered globally.

            Sharing

            Recommended Videos

            Presentations on similar topic, category or speaker

            SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
            07:00

            SIGUA: Forgetting May Make Learning with Noisy Labels More Robust

            Bo Han, …

            I2
            I2
            ICML 2020 5 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            Learning Calibratable Policies with Programmatic Style-Consistency
            15:04

            Learning Calibratable Policies with Programmatic Style-Consistency

            Eric Zhan, …

            I2
            I2
            ICML 2020 5 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
            15:35

            The Usual Suspects? Reassessing Blame for VAE Posterior Collapse

            Bin Dai, …

            I2
            I2
            ICML 2020 5 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            Sequence Generation with Mixed Representations
            13:54

            Sequence Generation with Mixed Representations

            Lijun Wu, …

            I2
            I2
            ICML 2020 5 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            Not Your Grandfather's Test Set: Reducing Labeling Effort for Testing
            11:39

            Not Your Grandfather's Test Set: Reducing Labeling Effort for Testing

            Begum Taskazan, …

            I2
            I2
            ICML 2020 5 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            Layered Sampling for Robust Optimization Problems
            12:59

            Layered Sampling for Robust Optimization Problems

            Hu Ding, …

            I2
            I2
            ICML 2020 5 years ago

            Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%

            Interested in talks like this? Follow ICML 2020