Next
Livestream will start soon!
Livestream has already ended.
Presentation has not been recorded yet!
  • title: Unleashing the Autoconversion Rates Forecasting: Evidential Regression from Satellite Data
      0:00 / 0:00
      • Report Issue
      • Settings
      • Playlists
      • Bookmarks
      • Subtitles Off
      • Playback rate
      • Quality
      • Settings
      • Debug information
      • Server sl-yoda-v3-stream-003-alpha.b-cdn.net
      • Subtitles size Medium
      • Bookmarks
      • Server
      • sl-yoda-v3-stream-003-alpha.b-cdn.net
      • sl-yoda-v3-stream-003-beta.b-cdn.net
      • 1781061970.rsc.cdn77.org
      • 1757035128.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
            Unleashing the Autoconversion Rates Forecasting: Evidential Regression from Satellite Data
            • Settings
            • Sync diff
            • Quality
            • Settings
            • Server
            • Quality
            • Server

            Unleashing the Autoconversion Rates Forecasting: Evidential Regression from Satellite Data

            Dez 15, 2023

            Sprecher:innen

            MCN

            Maria Carolina Novitasari

            Řečník · 0 sledujících

            JQ

            Johannes Quaas

            Řečník · 0 sledujících

            MRDR

            Miguel R. D. Rodrigues

            Řečník · 0 sledujících

            Über

            High-resolution simulations such as the ICOsahedral Non-hydrostatic Large-Eddy Model (ICON-LEM) can be used to study the interactions between aerosols, clouds, and precipitation processes that currently represent the largest source of uncertainty involved in climate change projections. However, due to significant computational costs, it can only be employed for a limited period and area. While machine learning mitigates this, model uncertainties may affect reliability. To address this, we develo…

            Organisator

            N2
            N2

            NeurIPS 2023

            Účet · 645 sledujících

            Gefällt euch das Format? Vertraut auf SlidesLive, um euer nächstes Event festzuhalten!

            Professionelle Aufzeichnung und Livestreaming – weltweit.

            Freigeben

            Empfohlene Videos

            Präsentationen, deren Thema, Kategorie oder Sprecher:in ähnlich sind

            LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite
            04:59

            LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite

            Artur Petrov Toshev, …

            N2
            N2
            NeurIPS 2023 16 months ago

            Pro uložení prezentace do věčného trezoru hlasovalo 0 diváků, což je 0.0 %

            Softmax Output Approximation for Activation Memory-Efficient Training of Attention-based Networks
            04:50

            Softmax Output Approximation for Activation Memory-Efficient Training of Attention-based Networks

            Changhyeon Lee, …

            N2
            N2
            NeurIPS 2023 16 months ago

            Pro uložení prezentace do věčného trezoru hlasovalo 0 diváků, což je 0.0 %

            Closing remarks from organizers
            00:53

            Closing remarks from organizers

            Aram-Alexandre Pooladian

            N2
            N2
            NeurIPS 2023 16 months ago

            Pro uložení prezentace do věčného trezoru hlasovalo 0 diváků, což je 0.0 %

            SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks
            05:03

            SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks

            Bill Yuchen Lin, …

            N2
            N2
            NeurIPS 2023 16 months ago

            Pro uložení prezentace do věčného trezoru hlasovalo 0 diváků, což je 0.0 %

            Provable benefits of annealing for estimating normalizing constants
            04:00

            Provable benefits of annealing for estimating normalizing constants

            Omar Chehab, …

            N2
            N2
            NeurIPS 2023 16 months ago

            Pro uložení prezentace do věčného trezoru hlasovalo 0 diváků, což je 0.0 %

            Panel Discussion
            59:47

            Panel Discussion

            Cheng Zhang, …

            N2
            N2
            NeurIPS 2023 16 months ago

            Pro uložení prezentace do věčného trezoru hlasovalo 0 diváků, což je 0.0 %

            Interessiert an Vorträgen wie diesem? NeurIPS 2023 folgen