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Q/A and Discussion for ML Theory Session
Karthik Kashinath · Mayur Mudigonda · Stephan Mandt · Rose Yu
Moderated by Karthik Kashinath and Mayur Mudigonda
Author Information
Karthik Kashinath (LBNL)
Mayur Mudigonda (UC Berkeley)
Stephan Mandt (University of California, Irivine)
Rose Yu (University of California, San Diego)
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2020 : Paper 60: Traffic Forecasting using Vehicle-to-Vehicle Communication and Recurrent Neural Networks »
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2021 : Analyzing High-Resolution Clouds and Convection using Multi-Channel VAEs »
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2021 : Structured Stochastic Gradient MCMC: a hybrid VI and MCMC approach »
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2022 : A Noether's theorem for gradient flow: Continuous symmetries of the architecture and conserved quantities of gradient flow »
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2022 : Probabilistic Querying of Continuous-Time Sequential Events »
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2022 : An Unsupervised Learning Perspective on the Dynamic Contribution to Extreme Precipitation Changes »
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2022 : FourCastNet: A practical introduction to a state-of-the-art deep learning global weather emulator »
Jaideep Pathak · Shashank Subramanian · Peter Harrington · Thorsten Kurth · Andre Graubner · Morteza Mardani · David Hall · Karthik Kashinath · Anima Anandkumar -
2022 : Charting Flat Minima Using the Conserved Quantities of Gradient Flow »
Bo Zhao · Iordan Ganev · Robin Walters · Rose Yu · Nima Dehmamy -
2022 : Rethinking Neural Relational Inference for Granger Causal Discovery »
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2023 Workshop: Deep Generative Models for Health »
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2022 : Rose Yu: "Physics-Guided Deep Learning for Climate Science" »
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2022 : Keynote Talk 2 »
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2022 : Q & A »
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2022 Tutorial: Data Compression with Machine Learning »
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2022 : Tutorial part 1 »
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2022 : Panel Discussion I: Geometric and topological principles for representation learning in ML »
Irina Higgins · Taco Cohen · Erik Bekkers · Nina Miolane · Rose Yu -
2022 Poster: Meta-Learning Dynamics Forecasting Using Task Inference »
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2022 Poster: Symmetry Teleportation for Accelerated Optimization »
Bo Zhao · Nima Dehmamy · Robin Walters · Rose Yu -
2022 Poster: Predictive Querying for Autoregressive Neural Sequence Models »
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2021 : Physics-Guided AI for Modeling Autonomous Vehicle Dynamics »
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2021 Poster: Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning »
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2020 : Q/A and Discussion for Benchmark Datasets »
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2020 : Benchmark Datasets »
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2020 : Q/A and Panel Discussion for People-Earth with Dan Kammen and Milind Tambe »
Daniel Kammen · Milind Tambe · Giulio De Leo · Mayur Mudigonda · Surya Karthik Mukkavilli -
2020 : People-Earth »
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2020 : Rose Yu »
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2020 : Stephan Mandt »
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2020 : Simulations, Physics-guided, and ML Theory »
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2020 : Q/A and Discussion »
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2020 : Rose Yu - Physics-Guided AI for Learning Spatiotemporal Dynamics »
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2020 Workshop: AI for Earth Sciences »
Surya Karthik Mukkavilli · Johanna Hansen · Natasha Dudek · Tom Beucler · Kelly Kochanski · Mayur Mudigonda · Karthik Kashinath · Amy McGovern · Paul D Miller · Chad Frischmann · Pierre Gentine · Gregory Dudek · Aaron Courville · Daniel Kammen · Vipin Kumar -
2020 Workshop: Machine Learning for Engineering Modeling, Simulation and Design »
Alex Beatson · Priya Donti · Amira Abdel-Rahman · Stephan Hoyer · Rose Yu · J. Zico Kolter · Ryan Adams -
2020 : Invited Talk 11 Q&A by Rose »
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2020 : Invited Talk 11: Tensor Methods for Efficient and Interpretable Spatiotemporal Learning »
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2020 Workshop: Machine Learning and the Physical Sciences »
Anima Anandkumar · Kyle Cranmer · Shirley Ho · Mr. Prabhat · Lenka Zdeborová · Atilim Gunes Baydin · Juan Carrasquilla · Adji Bousso Dieng · Karthik Kashinath · Gilles Louppe · Brian Nord · Michela Paganini · Savannah Thais -
2020 : Quantifying Uncertainty in Deep Spatiotemporal Forecasting for COVID-19 »
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2020 Poster: Deep Imitation Learning for Bimanual Robotic Manipulation »
Fan Xie · Alexander Chowdhury · M. Clara De Paolis Kaluza · Linfeng Zhao · Lawson Wong · Rose Yu -
2020 Poster: Learning Disentangled Representations of Videos with Missing Data »
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2020 Session: Orals & Spotlights Track 06: Dynamical Sys/Density/Sparsity »
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2019 : Opening Remarks »
Atilim Gunes Baydin · Juan Carrasquilla · Shirley Ho · Karthik Kashinath · Michela Paganini · Savannah Thais · Anima Anandkumar · Kyle Cranmer · Roger Melko · Mr. Prabhat · Frank Wood -
2019 Workshop: Machine Learning and the Physical Sciences »
Atilim Gunes Baydin · Juan Carrasquilla · Shirley Ho · Karthik Kashinath · Michela Paganini · Savannah Thais · Anima Anandkumar · Kyle Cranmer · Roger Melko · Mr. Prabhat · Frank Wood -
2018 : Long Range Sequence Generation via Multiresolution Adversarial Training »
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2017 : Poster session 2 and coffee break »
Sean McGregor · Tobias Hagge · Markus Stoye · Trang Thi Minh Pham · Seungkyun Hong · Amir Farbin · Sungyong Seo · Susana Zoghbi · Daniel George · Stanislav Fort · Steven Farrell · Arthur Pajot · Kyle Pearson · Adam McCarthy · Cecile Germain · Dustin Anderson · Mario Lezcano Casado · Mayur Mudigonda · Benjamin Nachman · Luke de Oliveira · Li Jing · Lingge Li · Soo Kyung Kim · Timothy Gebhard · Tom Zahavy -
2017 : Poster session 1 and coffee break »
Tobias Hagge · Sean McGregor · Markus Stoye · Trang Thi Minh Pham · Seungkyun Hong · Amir Farbin · Sungyong Seo · Susana Zoghbi · Daniel George · Stanislav Fort · Steven Farrell · Arthur Pajot · Kyle Pearson · Adam McCarthy · Cecile Germain · Dustin Anderson · Mario Lezcano Casado · Mayur Mudigonda · Benjamin Nachman · Luke de Oliveira · Li Jing · Lingge Li · Soo Kyung Kim · Timothy Gebhard · Tom Zahavy