Next
Livestream will start soon!
Livestream has already ended.
Presentation has not been recorded yet!
  • title: Neural Latent Aligner: Cross-trial Alignment for Learning Representations of Complex, Naturalistic Neural Data
      0:00 / 0:00
      • Report Issue
      • Settings
      • Playlists
      • Bookmarks
      • Subtitles Off
      • Playback rate
      • Quality
      • Settings
      • Debug information
      • Server sl-yoda-v2-stream-001-alpha.b-cdn.net
      • Subtitles size Medium
      • Bookmarks
      • Server
      • sl-yoda-v2-stream-001-alpha.b-cdn.net
      • sl-yoda-v2-stream-001-beta.b-cdn.net
      • 1824830694.rsc.cdn77.org
      • 1979322955.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
            Neural Latent Aligner: Cross-trial Alignment for Learning Representations of Complex, Naturalistic Neural Data
            • Settings
            • Sync diff
            • Quality
            • Settings
            • Server
            • Quality
            • Server

            Neural Latent Aligner: Cross-trial Alignment for Learning Representations of Complex, Naturalistic Neural Data

            Jul 24, 2023

            Speakers

            CJC

            Cheol Jun Cho

            Speaker · 0 followers

            EC

            Edward Chang

            Speaker · 0 followers

            GAA

            Gopala A. Anumanchipalli

            Speaker · 0 followers

            About

            Understanding the neural implementation of complex human behaviors is one of the major goals of neuroscience. To this end, it is crucial to find a true representation of the neural data, which is challenging due to the high complexity of the task and the low signal-to-ratio (SNR) of the signals. Here, we propose a novel unsupervised learning framework, Neural Latent Aligner (NLA), to find well-constrained, behaviorally relevant neural representations of complex behaviors. The key idea is to alig…

            Organizer

            I2
            I2

            ICML 2023

            Account · 627 followers

            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

            Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
            11:25

            Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network

            Tristan Deleu, …

            I2
            I2
            ICML 2023 2 years ago

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

            Generalization and Corruption Resistance via Distributionally Robust Optimization
            05:46

            Generalization and Corruption Resistance via Distributionally Robust Optimization

            Amine Bennouna, …

            I2
            I2
            ICML 2023 2 years ago

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

            Task-Specific Skill Localization in Fine-tuned Language Models
            05:34

            Task-Specific Skill Localization in Fine-tuned Language Models

            Abhishek Panigrahi, …

            I2
            I2
            ICML 2023 2 years ago

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

            Traversing Between Modes in Function Space for Fast Ensembling
            05:14

            Traversing Between Modes in Function Space for Fast Ensembling

            EungGu Yun, …

            I2
            I2
            ICML 2023 2 years ago

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

            A Study on Transformer Configuration and Training Objective
            05:18

            A Study on Transformer Configuration and Training Objective

            Fuzhao Xue, …

            I2
            I2
            ICML 2023 2 years ago

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

            Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions
            05:10

            Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions

            Boxiang Lyu, …

            I2
            I2
            ICML 2023 2 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 2023