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Session 1 | Invited talk: Max Welling, "Accelerating simulations of nature, both classical and quantum, with equivariant deep learning"
Max Welling · Atilim Gunes Baydin
Author Information
Max Welling (University of Amsterdam / Qualcomm AI Research)
Atilim Gunes Baydin (University of Oxford)
More from the Same Authors
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2021 : Learning the solar latent space: sigma-variational autoencoders for multiple channel solar imaging »
Edward Brown · Christopher Bridges · Bernard Benson · Atilim Gunes Baydin -
2021 : Simultaneous Multivariate Forecast of Space Weather Indices using Deep Neural Network Ensembles »
Bernard Benson · Christopher Bridges · Atilim Gunes Baydin -
2021 : Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data »
Sindy Löwe · David Madras · Richard Zemel · Max Welling -
2021 : Dropout and Ensemble Networks for Thermospheric Density Uncertainty Estimation »
Stefano Bonasera · Giacomo Acciarini · Jorge Pérez-Hernández · Bernard Benson · Edward Brown · Eric Sutton · Moriba Jah · Christopher Bridges · Atilim Gunes Baydin -
2021 : Particle Dynamics for Learning EBMs »
Kirill Neklyudov · Priyank Jaini · Max Welling -
2022 : PIPS: Path Integral Stochastic Optimal Control for Path Sampling in Molecular Dynamics »
Lars Holdijk · Yuanqi Du · Ferry Hooft · Priyank Jaini · Berend Ensing · Max Welling -
2022 : Inferring molecular complexity from mass spectrometry data using machine learning »
Timothy Gebhard · Aaron C. Bell · Jian Gong · Jaden J. A. Hastings · George Fricke · Nathalie Cabrol · Scott Sandford · Michael Phillips · Kimberley Warren-Rhodes · Atilim Gunes Baydin -
2022 : Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design »
Ilia Igashov · Hannes Stärk · Clément Vignac · Victor Garcia Satorras · Pascal Frossard · Max Welling · Michael Bronstein · Bruno Correia -
2022 : Program Synthesis for Integer Sequence Generation »
Natasha Butt · Auke Wiggers · Taco Cohen · Max Welling -
2022 : Structure-based Drug Design with Equivariant Diffusion Models »
Arne Schneuing · Yuanqi Du · Charles Harris · Arian Jamasb · Ilia Igashov · weitao Du · Tom Blundell · Pietro Lió · Carla Gomes · Max Welling · Michael Bronstein · Bruno Correia -
2022 Spotlight: Alleviating Adversarial Attacks on Variational Autoencoders with MCMC »
Anna Kuzina · Max Welling · Jakub Tomczak -
2022 : Invited Speaker »
Max Welling -
2022 Workshop: Machine Learning and the Physical Sciences »
Atilim Gunes Baydin · Adji Bousso Dieng · Emine Kucukbenli · Gilles Louppe · Siddharth Mishra-Sharma · Benjamin Nachman · Brian Nord · Savannah Thais · Anima Anandkumar · Kyle Cranmer · Lenka Zdeborová · Rianne van den Berg -
2022 : Invited Talk #4, The Fifth Paradigm of Scientific Discovery, Max Welling »
Max Welling -
2022 Workshop: AI for Science: Progress and Promises »
Yi Ding · Yuanqi Du · Tianfan Fu · Hanchen Wang · Anima Anandkumar · Yoshua Bengio · Anthony Gitter · Carla Gomes · Aviv Regev · Max Welling · Marinka Zitnik -
2022 Poster: Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel »
Changyong Oh · Roberto Bondesan · Efstratios Gavves · Max Welling -
2022 Poster: Alleviating Adversarial Attacks on Variational Autoencoders with MCMC »
Anna Kuzina · Max Welling · Jakub Tomczak -
2022 Poster: On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane »
Gabriele Cesa · Arash Behboodi · Taco Cohen · Max Welling -
2021 : Particle Dynamics for Learning EBMs »
Kirill Neklyudov · Priyank Jaini · Max Welling -
2021 : General Discussion 1 - What is out of distribution (OOD) generalization and why is it important? with Yoshua Bengio, Leyla Isik, Max Welling »
Yoshua Bengio · Leyla Isik · Max Welling · Joshua T Vogelstein · Weiwei Yang -
2021 Workshop: Bayesian Deep Learning »
Yarin Gal · Yingzhen Li · Sebastian Farquhar · Christos Louizos · Eric Nalisnick · Andrew Gordon Wilson · Zoubin Ghahramani · Kevin Murphy · Max Welling -
2021 : Session 3 | Contributed talk: Maximilian Dax, "Amortized Bayesian inference of gravitational waves with normalizing flows" »
Maximilian Dax · Atilim Gunes Baydin -
2021 : Session 3 | Invited talk: Laure Zanna, "The future of climate modeling in the age of machine learning" »
Laure Zanna · Atilim Gunes Baydin -
2021 : Session 3 | Invited talk: Surya Ganguli, "From the geometry of high dimensional energy landscapes to optimal annealing in a dissipative many body quantum optimizer" »
Surya Ganguli · Atilim Gunes Baydin -
2021 : Session 2 | Contributed talk: George Stein, "Self-supervised similarity search for large scientific datasets" »
George Stein · Atilim Gunes Baydin -
2021 : Session 2 | Invited talk: Megan Ansdell, "NASA's efforts & opportunities to support ML in the Physical Sciences" »
Megan Ansdell · Atilim Gunes Baydin -
2021 : Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders »
T. Anderson Keller · Qinghe Gao · Max Welling -
2021 : Session 1 | Contributed talk: Tian Xie, "Crystal Diffusion Variational Autoencoder for Periodic Material Generation" »
Tian Xie · Atilim Gunes Baydin -
2021 : Live Panel »
Max Welling · Bharath Ramsundar · Irina Rish · Karianne J Bergen · Pushmeet Kohli -
2021 : Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders »
T. Anderson Keller · Qinghe Gao · Max Welling -
2021 : Session 1 | Invited talk: Bingqing Cheng, "Predicting material properties with the help of machine learning" »
Bingqing Cheng · Atilim Gunes Baydin -
2021 Workshop: Machine Learning and the Physical Sciences »
Anima Anandkumar · Kyle Cranmer · Mr. Prabhat · Lenka Zdeborová · Atilim Gunes Baydin · Juan Carrasquilla · Emine Kucukbenli · Gilles Louppe · Benjamin Nachman · Brian Nord · Savannah Thais -
2021 Workshop: AI for Science: Mind the Gaps »
Payal Chandak · Yuanqi Du · Tianfan Fu · Wenhao Gao · Kexin Huang · Shengchao Liu · Ziming Liu · Gabriel Spadon · Max Tegmark · Hanchen Wang · Adrian Weller · Max Welling · Marinka Zitnik -
2021 Poster: Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions »
Emiel Hoogeboom · Didrik Nielsen · Priyank Jaini · Patrick Forré · Max Welling -
2021 Poster: Topographic VAEs learn Equivariant Capsules »
T. Anderson Keller · Max Welling -
2021 : Unsupervised Indoor Wi-Fi Positioning »
Farhad G. Zanjani · Ilia Karmanov · Hanno Ackermann · Daniel Dijkman · Max Welling · Ishaque Kadampot · Simone Merlin · Steve Shellhammer · Rui Liang · Brian Buesker · Harshit Joshi · Vamsi Vegunta · Raamkumar Balamurthi · Bibhu Mohanty · Joseph Soriaga · Ron Tindall · Pat Lawlor -
2021 Poster: Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent »
Priyank Jaini · Lars Holdijk · Max Welling -
2021 Poster: E(n) Equivariant Normalizing Flows »
Victor Garcia Satorras · Emiel Hoogeboom · Fabian Fuchs · Ingmar Posner · Max Welling -
2021 Poster: Modality-Agnostic Topology Aware Localization »
Farhad Ghazvinian Zanjani · Ilia Karmanov · Hanno Ackermann · Daniel Dijkman · Simone Merlin · Max Welling · Fatih Porikli -
2021 Poster: Domain Invariant Representation Learning with Domain Density Transformations »
A. Tuan Nguyen · Toan Tran · Yarin Gal · Atilim Gunes Baydin -
2021 Oral: E(n) Equivariant Normalizing Flows »
Victor Garcia Satorras · Emiel Hoogeboom · Fabian Fuchs · Ingmar Posner · Max Welling -
2020 : Invited Talk: Max Welling - The LIAR (Learning with Interval Arithmetic Regularization) is Dead »
Max Welling -
2020 : Session 3 | Invited talk: Laura Waller, "Physics-based Learning for Computational Microscopy" »
Laura Waller · Atilim Gunes Baydin -
2020 : Session 2 | Invited talk: Phiala Shanahan, "Generative Flow Models for Gauge Field Theory" »
Phiala Shanahan · Atilim Gunes Baydin -
2020 : Session 2 | Invited talk: Estelle Inack, "Variational Neural Annealing" »
Estelle Inack · Atilim Gunes Baydin -
2020 : Session 1 | Invited talk: Michael Bronstein, "Geometric Deep Learning for Functional Protein Design" »
Michael Bronstein · Atilim Gunes Baydin -
2020 : Session 1 | Invited talk: Lauren Anderson, "3D Milky Way Dust Map using a Scalable Gaussian Process" »
Lauren Anderson · Atilim Gunes Baydin -
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 Poster: Natural Graph Networks »
Pim de Haan · Taco Cohen · Max Welling -
2020 Poster: SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks »
Fabian Fuchs · Daniel E Worrall · Volker Fischer · Max Welling -
2020 Poster: SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows »
Didrik Nielsen · Priyank Jaini · Emiel Hoogeboom · Ole Winther · Max Welling -
2020 Oral: SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows »
Didrik Nielsen · Priyank Jaini · Emiel Hoogeboom · Ole Winther · Max Welling -
2020 Poster: The Convolution Exponential and Generalized Sylvester Flows »
Emiel Hoogeboom · Victor Garcia Satorras · Jakub Tomczak · Max Welling -
2020 Poster: Black-Box Optimization with Local Generative Surrogates »
Sergey Shirobokov · Vladislav Belavin · Michael Kagan · Andrei Ustyuzhanin · Atilim Gunes Baydin -
2020 Poster: Bayesian Bits: Unifying Quantization and Pruning »
Mart van Baalen · Christos Louizos · Markus Nagel · Rana Ali Amjad · Ying Wang · Tijmen Blankevoort · Max Welling -
2020 Poster: Experimental design for MRI by greedy policy search »
Tim Bakker · Herke van Hoof · Max Welling -
2020 Spotlight: Experimental design for MRI by greedy policy search »
Tim Bakker · Herke van Hoof · Max Welling -
2020 Poster: MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning »
Elise van der Pol · Daniel E Worrall · Herke van Hoof · Frans Oliehoek · Max Welling -
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 -
2019 Workshop: Program Transformations for ML »
Pascal Lamblin · Atilim Gunes Baydin · Alexander Wiltschko · Bart van Merriënboer · Emily Fertig · Barak Pearlmutter · David Duvenaud · Laurent Hascoet -
2019 : TBD »
Max Welling -
2019 : Keynote - ML »
Max Welling -
2019 Workshop: Bayesian Deep Learning »
Yarin Gal · José Miguel Hernández-Lobato · Christos Louizos · Eric Nalisnick · Zoubin Ghahramani · Kevin Murphy · Max Welling -
2019 Poster: Invert to Learn to Invert »
Patrick Putzky · Max Welling -
2019 Poster: Deep Scale-spaces: Equivariance Over Scale »
Daniel Worrall · Max Welling -
2019 Poster: Integer Discrete Flows and Lossless Compression »
Emiel Hoogeboom · Jorn Peters · Rianne van den Berg · Max Welling -
2019 Poster: The Functional Neural Process »
Christos Louizos · Xiahan Shi · Klamer Schutte · Max Welling -
2019 Poster: Combining Generative and Discriminative Models for Hybrid Inference »
Victor Garcia Satorras · Zeynep Akata · Max Welling -
2019 Spotlight: Combining Generative and Discriminative Models for Hybrid Inference »
Victor Garcia Satorras · Max Welling · Zeynep Akata -
2019 Poster: Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model »
Atilim Gunes Baydin · Lei Shao · Wahid Bhimji · Lukas Heinrich · Saeid Naderiparizi · Andreas Munk · Jialin Liu · Bradley Gram-Hansen · Gilles Louppe · Lawrence Meadows · Philip Torr · Victor Lee · Kyle Cranmer · Mr. Prabhat · Frank Wood -
2019 Poster: Combinatorial Bayesian Optimization using the Graph Cartesian Product »
Changyong Oh · Jakub Tomczak · Stratis Gavves · Max Welling -
2018 : Making the Case for using more Inductive Bias in Deep Learning »
Max Welling -
2018 : Panel disucssion »
Max Welling · Tim Genewein · Edwin Park · Song Han -
2018 : Efficient Computation of Deep Convolutional Neural Networks: A Quantization Perspective »
Max Welling -
2018 : Prof. Max Welling »
Max Welling -
2018 Workshop: Bayesian Deep Learning »
Yarin Gal · José Miguel Hernández-Lobato · Christos Louizos · Andrew Wilson · Zoubin Ghahramani · Kevin Murphy · Max Welling -
2018 Workshop: NIPS 2018 workshop on Compact Deep Neural Networks with industrial applications »
Lixin Fan · Zhouchen Lin · Max Welling · Yurong Chen · Werner Bailer -
2018 Poster: Graphical Generative Adversarial Networks »
Chongxuan LI · Max Welling · Jun Zhu · Bo Zhang -
2018 Poster: 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data »
Maurice Weiler · Wouter Boomsma · Mario Geiger · Max Welling · Taco Cohen -
2017 : Panel discussion »
Atilim Gunes Baydin · Adam Paszke · Jonathan Hüser · Jean Utke · Laurent Hascoet · Jeffrey Siskind · Jan Hueckelheim · Andreas Griewank -
2017 : Panel Session »
Neil Lawrence · Finale Doshi-Velez · Zoubin Ghahramani · Yann LeCun · Max Welling · Yee Whye Teh · Ole Winther -
2017 : Deep Bayes for Distributed Learning, Uncertainty Quantification and Compression »
Max Welling -
2017 : Beyond backprop: automatic differentiation in machine learning »
Atilim Gunes Baydin -
2017 Workshop: Bayesian Deep Learning »
Yarin Gal · José Miguel Hernández-Lobato · Christos Louizos · Andrew Wilson · Andrew Wilson · Diederik Kingma · Zoubin Ghahramani · Kevin Murphy · Max Welling -
2017 : Panel session »
Iain Murray · Max Welling · Juan Carrasquilla · Anatole von Lilienfeld · Gilles Louppe · Kyle Cranmer -
2017 : Panel: On the Foundations and Future of Approximate Inference »
David Blei · Zoubin Ghahramani · Katherine Heller · Tim Salimans · Max Welling · Matthew D. Hoffman -
2017 : Invited talk 1: Deep recurrent inverse modeling for radio astronomy and fast MRI imaging »
Max Welling -
2017 Workshop: Deep Learning for Physical Sciences »
Atilim Gunes Baydin · Mr. Prabhat · Kyle Cranmer · Frank Wood -
2017 Workshop: Advances in Approximate Bayesian Inference »
Francisco Ruiz · Stephan Mandt · Cheng Zhang · James McInerney · James McInerney · Dustin Tran · Dustin Tran · David Blei · Max Welling · Tamara Broderick · Michalis Titsias -
2017 Poster: Causal Effect Inference with Deep Latent-Variable Models »
Christos Louizos · Uri Shalit · Joris Mooij · David Sontag · Richard Zemel · Max Welling -
2017 Poster: Bayesian Compression for Deep Learning »
Christos Louizos · Karen Ullrich · Max Welling -
2016 : Max Welling : Making Deep Learning Efficient Through Sparsification »
Max Welling -
2016 Workshop: Bayesian Deep Learning »
Yarin Gal · Christos Louizos · Zoubin Ghahramani · Kevin Murphy · Max Welling -
2016 Poster: Improving Variational Autoencoders with Inverse Autoregressive Flow »
Diederik Kingma · Tim Salimans · Rafal Jozefowicz · Peter Chen · Xi Chen · Ilya Sutskever · Max Welling -
2015 Workshop: Scalable Monte Carlo Methods for Bayesian Analysis of Big Data »
Babak Shahbaba · Yee Whye Teh · Max Welling · Arnaud Doucet · Christophe Andrieu · Sebastian J. Vollmer · Pierre Jacob -
2015 : *Max Welling* Optimization Monte Carlo »
Max Welling -
2015 Symposium: Deep Learning Symposium »
Yoshua Bengio · Marc'Aurelio Ranzato · Honglak Lee · Max Welling · Andrew Y Ng -
2015 Poster: Bayesian dark knowledge »
Anoop Korattikara Balan · Vivek Rathod · Kevin Murphy · Max Welling -
2015 Poster: Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference »
Ted Meeds · Max Welling -
2015 Poster: Variational Dropout and the Local Reparameterization Trick »
Diederik Kingma · Tim Salimans · Max Welling -
2014 Workshop: ABC in Montreal »
Max Welling · Neil D Lawrence · Richard D Wilkinson · Ted Meeds · Christian X Robert -
2014 Poster: Semi-supervised Learning with Deep Generative Models »
Diederik Kingma · Shakir Mohamed · Danilo Jimenez Rezende · Max Welling -
2014 Demonstration: Machine Learning in the Browser »
Ted Meeds · Remco Hendriks · Said Al Faraby · Magiel Bruntink · Max Welling -
2014 Spotlight: Semi-supervised Learning with Deep Generative Models »
Diederik Kingma · Shakir Mohamed · Danilo Jimenez Rezende · Max Welling -
2013 Workshop: Probabilistic Models for Big Data »
Neil D Lawrence · Joaquin Quiñonero-Candela · Tianshi Gao · James Hensman · Zoubin Ghahramani · Max Welling · David Blei · Ralf Herbrich -
2012 Poster: The Time-Marginalized Coalescent Prior for Hierarchical Clustering »
Levi Boyles · Max Welling -
2011 Poster: Statistical Tests for Optimization Efficiency »
Levi Boyles · Anoop Korattikara · Deva Ramanan · Max Welling -
2010 Poster: On Herding and the Perceptron Cycling Theorem »
Andrew E Gelfand · Yutian Chen · Laurens van der Maaten · Max Welling -
2008 Session: Oral session 10: Nonparametric Processes, Scene Processing and Image Statistics »
Max Welling -
2008 Poster: Asynchronous Distributed Learning of Topic Models »
Arthur Asuncion · Padhraic Smyth · Max Welling -
2007 Spotlight: Collapsed Variational Inference for HDP »
Yee Whye Teh · Kenichi Kurihara · Max Welling -
2007 Spotlight: Distributed Inference for Latent Dirichlet Allocation »
David Newman · Arthur Asuncion · Padhraic Smyth · Max Welling -
2007 Poster: Infinite State Bayes-Nets for Structured Domains »
Max Welling · Ian Porteous · Evgeniy Bart -
2007 Poster: Collapsed Variational Inference for HDP »
Yee Whye Teh · Kenichi Kurihara · Max Welling -
2007 Poster: Distributed Inference for Latent Dirichlet Allocation »
David Newman · Arthur Asuncion · Padhraic Smyth · Max Welling -
2007 Spotlight: Infinite State Bayes-Nets for Structured Domains »
Max Welling · Ian Porteous · Evgeniy Bart -
2006 Poster: Structure Learning in Markov Random Fields »
Sridevi Parise · Max Welling -
2006 Poster: Accelerated Variational Dirichlet Process Mixtures »
Kenichi Kurihara · Max Welling · Nikos Vlassis -
2006 Spotlight: Accelerated Variational Dirichlet Process Mixtures »
Kenichi Kurihara · Max Welling · Nikos Vlassis -
2006 Poster: A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation »
Yee Whye Teh · David Newman · Max Welling