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The Test of Time Award will be announced on Thursday, July 22nd at 11:00 PM ET.
Author Information
Max Welling (University of Amsterdam & Qualcomm)
Max Welling (University of Amsterdam)
Prof. Dr. Max Welling is a research chair in Machine Learning at the University of Amsterdam and a VP Technologies at Qualcomm. He has a secondary appointment as a senior fellow at the Canadian Institute for Advanced Research (CIFAR). He is co-founder of “Scyfer BV” a university spin-off in deep learning which got acquired by Qualcomm in summer 2017. In the past he held postdoctoral positions at Caltech (’98-’00), UCL (’00-’01) and the U. Toronto (’01-’03). He received his PhD in ’98 under supervision of Nobel laureate Prof. G. 't Hooft. Max Welling has served as associate editor in chief of IEEE TPAMI from 2011-2015 (impact factor 4.8). He serves on the board of the NIPS foundation since 2015 (the largest conference in machine learning) and has been program chair and general chair of NIPS in 2013 and 2014 respectively. He was also program chair of AISTATS in 2009 and ECCV in 2016 and general chair of MIDL 2018. He has served on the editorial boards of JMLR and JML and was an associate editor for Neurocomputing, JCGS and TPAMI. He received multiple grants from Google, Facebook, Yahoo, NSF, NIH, NWO and ONR-MURI among which an NSF career grant in 2005. He is recipient of the ECCV Koenderink Prize in 2010. Welling is in the board of the Data Science Research Center in Amsterdam, he directs the Amsterdam Machine Learning Lab (AMLAB), and co-directs the Qualcomm-UvA deep learning lab (QUVA) and the Bosch-UvA Deep Learning lab (DELTA). Max Welling has over 200 scientific publications in machine learning, computer vision, statistics and physics.
More from the Same Authors
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2022 : Path Integral Stochastic Optimal Control for Sampling Transition Paths »
Lars Holdijk · Yuanqi Du · Priyank Jaini · Ferry Hooft · Bernd Ensing · Max Welling -
2023 : Lie Point Symmetry and Physics Informed Networks »
Tara Akhound-Sadegh · Laurence Perreault-Levasseur · Johannes Brandstetter · Max Welling · Siamak Ravanbakhsh -
2023 Workshop: Structured Probabilistic Inference and Generative Modeling »
Dinghuai Zhang · Yuanqi Du · Chenlin Meng · Shawn Tan · Yingzhen Li · Max Welling · Yoshua Bengio -
2023 : Opening Remark »
Dinghuai Zhang · Yuanqi Du · Chenlin Meng · Shawn Tan · Yingzhen Li · Max Welling · Yoshua Bengio -
2023 Poster: Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally Coupled Oscillatory Recurrent Neural Networks »
T. Anderson Keller · Max Welling -
2023 Poster: Latent Traversals in Generative Models as Potential Flows »
Yue Song · T. Anderson Keller · Nicu Sebe · Max Welling -
2023 Poster: Geometric Clifford Algebra Networks »
David Ruhe · Jayesh K. Gupta · Steven De Keninck · Max Welling · Johannes Brandstetter -
2022 Poster: Lie Point Symmetry Data Augmentation for Neural PDE Solvers »
Johannes Brandstetter · Max Welling · Daniel Worrall -
2022 Spotlight: Lie Point Symmetry Data Augmentation for Neural PDE Solvers »
Johannes Brandstetter · Max Welling · Daniel Worrall -
2022 Poster: Equivariant Diffusion for Molecule Generation in 3D »
Emiel Hoogeboom · Victor Garcia Satorras · Clément Vignac · Max Welling -
2022 Oral: Equivariant Diffusion for Molecule Generation in 3D »
Emiel Hoogeboom · Victor Garcia Satorras · Clément Vignac · Max Welling -
2021 Test Of Time: Bayesian Learning via Stochastic Gradient Langevin Dynamics »
Yee Teh · Max Welling -
2021 Poster: The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning »
Roberto Bondesan · Max Welling -
2021 Spotlight: The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning »
Roberto Bondesan · Max Welling -
2021 Poster: A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups »
Marc Finzi · Max Welling · Andrew Wilson -
2021 Oral: A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups »
Marc Finzi · Max Welling · Andrew Wilson -
2021 Poster: Federated Learning of User Verification Models Without Sharing Embeddings »
Hossein Hosseini · Hyunsin Park · Sungrack Yun · Christos Louizos · Joseph B Soriaga · Max Welling -
2021 Poster: E(n) Equivariant Graph Neural Networks »
Victor Garcia Satorras · Emiel Hoogeboom · Max Welling -
2021 Poster: Self Normalizing Flows »
T. Anderson Keller · Jorn Peters · Priyank Jaini · Emiel Hoogeboom · Patrick Forré · Max Welling -
2021 Spotlight: E(n) Equivariant Graph Neural Networks »
Victor Garcia Satorras · Emiel Hoogeboom · Max Welling -
2021 Spotlight: Federated Learning of User Verification Models Without Sharing Embeddings »
Hossein Hosseini · Hyunsin Park · Sungrack Yun · Christos Louizos · Joseph B Soriaga · Max Welling -
2021 Spotlight: Self Normalizing Flows »
T. Anderson Keller · Jorn Peters · Priyank Jaini · Emiel Hoogeboom · Patrick Forré · Max Welling -
2020 : Invited talk 1: Unifying VAEs and Flows »
Max Welling -
2020 Poster: Involutive MCMC: a Unifying Framework »
Kirill Neklyudov · Max Welling · Evgenii Egorov · Dmitry Vetrov -
2019 Workshop: Learning and Reasoning with Graph-Structured Representations »
Ethan Fetaya · Zhiting Hu · Thomas Kipf · Yujia Li · Xiaodan Liang · Renjie Liao · Raquel Urtasun · Hao Wang · Max Welling · Eric Xing · Richard Zemel -
2019 : Poster discussion »
Roman Novak · Maxime Gabella · Frederic Dreyer · Siavash Golkar · Anh Tong · Irina Higgins · Mirco Milletari · Joe Antognini · Sebastian Goldt · Adín Ramírez Rivera · Roberto Bondesan · Ryo Karakida · Remi Tachet des Combes · Michael Mahoney · Nicholas Walker · Stanislav Fort · Samuel Smith · Rohan Ghosh · Aristide Baratin · Diego Granziol · Stephen Roberts · Dmitry Vetrov · Andrew Wilson · César Laurent · Valentin Thomas · Simon Lacoste-Julien · Dar Gilboa · Daniel Soudry · Anupam Gupta · Anirudh Goyal · Yoshua Bengio · Erich Elsen · Soham De · Stanislaw Jastrzebski · Charles H Martin · Samira Shabanian · Aaron Courville · Shorato Akaho · Lenka Zdeborova · Ethan Dyer · Maurice Weiler · Pim de Haan · Taco Cohen · Max Welling · Ping Luo · zhanglin peng · Nasim Rahaman · Loic Matthey · Danilo J. Rezende · Jaesik Choi · Kyle Cranmer · Lechao Xiao · Jaehoon Lee · Yasaman Bahri · Jeffrey Pennington · Greg Yang · Jiri Hron · Jascha Sohl-Dickstein · Guy Gur-Ari -
2019 : Panel Discussion (moderator: Tom Dietterich) »
Max Welling · Kilian Weinberger · Terrance Boult · Dawn Song · Thomas Dietterich -
2019 : Keynote by Max Welling: A Nonparametric Bayesian Approach to Deep Learning (without GPs) »
Max Welling -
2019 Workshop: Joint Workshop on On-Device Machine Learning & Compact Deep Neural Network Representations (ODML-CDNNR) »
Sujith Ravi · Zornitsa Kozareva · Lixin Fan · Max Welling · Yurong Chen · Werner Bailer · Brian Kulis · Haoji Hu · Jonathan Dekhtiar · Yingyan Lin · Diana Marculescu -
2019 Workshop: Theoretical Physics for Deep Learning »
Jaehoon Lee · Jeffrey Pennington · Yasaman Bahri · Max Welling · Surya Ganguli · Joan Bruna -
2019 : Opening Remarks »
Jaehoon Lee · Jeffrey Pennington · Yasaman Bahri · Max Welling · Surya Ganguli · Joan Bruna -
2019 Poster: Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement »
Wouter Kool · Herke van Hoof · Max Welling -
2019 Oral: Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement »
Wouter Kool · Herke van Hoof · Max Welling -
2019 Poster: Emerging Convolutions for Generative Normalizing Flows »
Emiel Hoogeboom · Rianne Van den Berg · Max Welling -
2019 Oral: Emerging Convolutions for Generative Normalizing Flows »
Emiel Hoogeboom · Rianne Van den Berg · Max Welling -
2019 Poster: Gauge Equivariant Convolutional Networks and the Icosahedral CNN »
Taco Cohen · Maurice Weiler · Berkay Kicanaoglu · Max Welling -
2019 Oral: Gauge Equivariant Convolutional Networks and the Icosahedral CNN »
Taco Cohen · Maurice Weiler · Berkay Kicanaoglu · Max Welling -
2018 Poster: Attention-based Deep Multiple Instance Learning »
Maximilian Ilse · Jakub Tomczak · Max Welling -
2018 Oral: Attention-based Deep Multiple Instance Learning »
Maximilian Ilse · Jakub Tomczak · Max Welling -
2018 Invited Talk: Intelligence per Kilowatthour »
Max Welling -
2018 Poster: Neural Relational Inference for Interacting Systems »
Thomas Kipf · Ethan Fetaya · Kuan-Chieh Wang · Max Welling · Richard Zemel -
2018 Poster: BOCK : Bayesian Optimization with Cylindrical Kernels »
ChangYong Oh · Efstratios Gavves · Max Welling -
2018 Oral: Neural Relational Inference for Interacting Systems »
Thomas Kipf · Ethan Fetaya · Kuan-Chieh Wang · Max Welling · Richard Zemel -
2018 Oral: BOCK : Bayesian Optimization with Cylindrical Kernels »
ChangYong Oh · Efstratios Gavves · Max Welling -
2017 Poster: Multiplicative Normalizing Flows for Variational Bayesian Neural Networks »
Christos Louizos · Max Welling -
2017 Talk: Multiplicative Normalizing Flows for Variational Bayesian Neural Networks »
Christos Louizos · Max Welling