Next
Livestream will start soon!
Livestream has already ended.
Presentation has not been recorded yet!
  • title: A Bit More Bayesian: Uncertainty for Domain-Invariant Learning
      0:00 / 0:00
      • Report Issue
      • Settings
      • Playlists
      • Bookmarks
      • Subtitles Off
      • Playback rate
      • Quality
      • Settings
      • Debug information
      • Server sl-yoda-v3-stream-013-alpha.b-cdn.net
      • Subtitles size Medium
      • Bookmarks
      • Server
      • sl-yoda-v3-stream-013-alpha.b-cdn.net
      • sl-yoda-v3-stream-013-beta.b-cdn.net
      • 1668715672.rsc.cdn77.org
      • 1420896597.rsc.cdn77.org
      • Subtitles
      • Off
      • English
      • Playback rate
      • Quality
      • Subtitles size
      • Large
      • Medium
      • Small
      • Mode
      • Video Slideshow
      • Audio Slideshow
      • Slideshow
      • Video
      My playlists
        Bookmarks
          00:00:00
            A Bit More Bayesian: Uncertainty for Domain-Invariant Learning
            • Settings
            • Sync diff
            • Quality
            • Settings
            • Server
            • Quality
            • Server

            A Bit More Bayesian: Uncertainty for Domain-Invariant Learning

            Jul 19, 2021

            Speakers

            ZX

            Zehao Xiao

            Sprecher:in · 0 Follower:innen

            JS

            Jiayi Shen

            Sprecher:in · 0 Follower:innen

            XZ

            Xiantong Zhen

            Sprecher:in · 0 Follower:innen

            Organizer

            I2
            I2

            ICML 2021

            Konto · 1,1k Follower:innen

            Categories

            Mathematik

            Kategorie · 2,4k Präsentationen

            KI und Datenwissenschaft

            Kategorie · 10,8k Präsentationen

            About ICML 2021

            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

            Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization
            05:17

            Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization

            Zeke Xie, …

            I2
            I2
            ICML 2021 4 years ago

            Ewigspeicher-Fortschrittswert: 0 = 0.0%

            Representation of Features as Images with Neighborhood Dependencies for Compatibility with Convolutional Neural Network
            05:24

            Representation of Features as Images with Neighborhood Dependencies for Compatibility with Convolutional Neural Network

            Omid Bazgir, …

            I2
            I2
            ICML 2021 4 years ago

            Ewigspeicher-Fortschrittswert: 0 = 0.0%

            Theory of Feature Selection
            26:41

            Theory of Feature Selection

            Rajiv Khanna

            I2
            I2
            ICML 2021 4 years ago

            Ewigspeicher-Fortschrittswert: 0 = 0.0%

            Fast-Slow Streamflow Model Using Mass-Conserving LSTM
            05:17

            Fast-Slow Streamflow Model Using Mass-Conserving LSTM

            Miguel Paredes Quinones, …

            I2
            I2
            ICML 2021 4 years ago

            Ewigspeicher-Fortschrittswert: 0 = 0.0%

            Trajectory Diversity for Zero-Shot Coordination
            05:16

            Trajectory Diversity for Zero-Shot Coordination

            Andrei Lupu, …

            I2
            I2
            ICML 2021 4 years ago

            Ewigspeicher-Fortschrittswert: 0 = 0.0%

            Interested in talks like this? Follow ICML 2021