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Deep Bayes for Distributed Learning, Uncertainty Quantification and Compression
Max Welling
Author Information
Max Welling (University of Amsterdam / Qualcomm AI Research)
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2021 : Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data »
Sindy Löwe · David Madras · Richard Zemel · Max Welling -
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 : 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 -
2023 Poster: Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation »
Kirill Neklyudov · Jannes Nys · Luca Thiede · Juan Carrasquilla · Qiang Liu · Max Welling · Alireza Makhzani -
2023 Poster: Rotating Features for Object Discovery »
Sindy Löwe · Phillip Lippe · Francesco Locatello · Max Welling -
2023 Poster: Lie Point Symmetry and Physics-Informed Networks »
Tara Akhound-Sadegh · Laurence Perreault-Levasseur · Johannes Brandstetter · Max Welling · Siamak Ravanbakhsh -
2023 Poster: Flow Factorized Representation Learning »
Yue Song · T. Anderson Keller · Nicu Sebe · Max Welling -
2023 Poster: Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths »
Lars Holdijk · Yuanqi Du · Ferry Hooft · Priyank Jaini · Berend Ensing · Max Welling -
2023 Oral: Rotating Features for Object Discovery »
Sindy Löwe · Phillip Lippe · Francesco Locatello · Max Welling -
2023 Workshop: AI for Science: from Theory to Practice »
Yuanqi Du · Max Welling · Yoshua Bengio · Marinka Zitnik · Carla Gomes · Jure Leskovec · Maria Brbic · Wenhao Gao · Kexin Huang · Ziming Liu · Rocío Mercado · Miles Cranmer · Shengchao Liu · Lijing Wang -
2022 Spotlight: Alleviating Adversarial Attacks on Variational Autoencoders with MCMC »
Anna Kuzina · Max Welling · Jakub Tomczak -
2022 : Invited Speaker »
Max Welling -
2022 : Invited Talk #4, The Fifth Paradigm of Scientific Discovery, Max Welling »
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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 : Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders »
T. Anderson Keller · Qinghe Gao · Max Welling -
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: Max Welling, "Accelerating simulations of nature, both classical and quantum, with equivariant deep learning" »
Max Welling · Atilim Gunes Baydin -
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 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 »
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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: 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 : 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: 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 »
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2018 : Panel disucssion »
Max Welling · Tim Genewein · Edwin Park · Song Han -
2018 : Efficient Computation of Deep Convolutional Neural Networks: A Quantization Perspective »
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2018 : Prof. Max Welling »
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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 Session »
Neil Lawrence · Finale Doshi-Velez · Zoubin Ghahramani · Yann LeCun · Max Welling · Yee Whye Teh · Ole Winther -
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: 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