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Author Information
Max Welling (University of Amsterdam & Qualcomm)
Kilian Weinberger (Cornell University)
Kilian Weinberger is an Associate Professor in the Department of Computer Science at Cornell University. He received his Ph.D. from the University of Pennsylvania in Machine Learning under the supervision of Lawrence Saul and his undergraduate degree in Mathematics and Computer Science from the University of Oxford. During his career he has won several best paper awards at ICML, CVPR, AISTATS and KDD (runner-up award). In 2011 he was awarded the Outstanding AAAI Senior Program Chair Award and in 2012 he received an NSF CAREER award. He was elected co-Program Chair for ICML 2016 and for AAAI 2018. Kilian Weinberger's research focuses on Machine Learning and its applications. In particular, he focuses on learning under resource constraints, metric learning, machine learned web-search ranking, computer vision and deep learning. Before joining Cornell University, he was an Associate Professor at Washington University in St. Louis and before that he worked as a research scientist at Yahoo! Research in Santa Clara.
Terrance Boult (University of Colorado Colorado Springs)
Dawn Song (University of California, Berkeley)
Thomas Dietterich ((organization))
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: On the Effectiveness of Offline RL for Dialogue Response Generation »
Paloma Sodhi · Felix Wu · Ethan Elenberg · Kilian Weinberger · Ryan Mcdonald -
2023 Poster: Latent Traversals in Generative Models as Potential Flows »
Yue Song · T. Anderson Keller · Nicu Sebe · Max Welling -
2023 Poster: IncDSI: Incrementally Updatable Document Retrieval »
Varsha Kishore · Chao Wan · Justin Lovelace · Yoav Artzi · Kilian Weinberger -
2023 Poster: Unsupervised Out-of-Distribution Detection with Diffusion Inpainting »
Zhenzhen Liu · Jin Zhou · Yufan Wang · Kilian Weinberger -
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 : Live Panel Discussion »
Thomas Dietterich · Chelsea Finn · Kamalika Chaudhuri · Yarin Gal · Uri Shalit -
2021 : RL Foundation Panel »
Matthew Botvinick · Thomas Dietterich · Leslie Kaelbling · John Langford · Warrren B Powell · Csaba Szepesvari · Lihong Li · Yuxi Li -
2021 Test Of Time: Bayesian Learning via Stochastic Gradient Langevin Dynamics »
Yee Teh · Max Welling -
2021 Test Of Time: Test of Time Award »
Max Welling · Max Welling -
2021 Poster: Making Paper Reviewing Robust to Bid Manipulation Attacks »
Ruihan Wu · Chuan Guo · Felix Wu · Rahul Kidambi · Laurens van der Maaten · Kilian Weinberger -
2021 Spotlight: Making Paper Reviewing Robust to Bid Manipulation Attacks »
Ruihan Wu · Chuan Guo · Felix Wu · Rahul Kidambi · Laurens van der Maaten · Kilian Weinberger -
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: TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models »
Zhuohan Li · Siyuan Zhuang · Shiyuan Guo · Danyang Zhuo · Hao Zhang · Dawn Song · Ion Stoica -
2021 Poster: A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups »
Marc Finzi · Max Welling · Andrew Wilson -
2021 Poster: Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision »
Johan Björck · Xiangyu Chen · Christopher De Sa · Carla Gomes · Kilian Weinberger -
2021 Spotlight: Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision »
Johan Björck · Xiangyu Chen · Christopher De Sa · Carla Gomes · Kilian Weinberger -
2021 Spotlight: TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models »
Zhuohan Li · Siyuan Zhuang · Shiyuan Guo · Danyang Zhuo · Hao Zhang · Dawn Song · Ion Stoica -
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 Workshop: Incentives in Machine Learning »
Boi Faltings · Yang Liu · David Parkes · Goran Radanovic · Dawn Song -
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 : Keynote by Terrance Boult: The Deep Unknown: on Open-set and Adversarial Examples in Deep Learning »
Terrance Boult -
2019 : Keynote by Dawn Song: Adversarial Machine Learning: Challenges, Lessons, and Future Directions »
Dawn Song -
2019 : Keynote by Kilian Weinberger: On Calibration and Fairness »
Kilian Weinberger -
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: Workshop on the Security and Privacy of Machine Learning »
Nicolas Papernot · Florian Tramer · Bo Li · Dan Boneh · David Evans · Somesh Jha · Percy Liang · Patrick McDaniel · Jacob Steinhardt · Dawn Song -
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: Simple Black-box Adversarial Attacks »
Chuan Guo · Jacob Gardner · Yurong You · Andrew Wilson · Kilian Weinberger -
2019 Poster: Emerging Convolutions for Generative Normalizing Flows »
Emiel Hoogeboom · Rianne Van den Berg · Max Welling -
2019 Oral: Simple Black-box Adversarial Attacks »
Chuan Guo · Jacob Gardner · Yurong You · Andrew Wilson · Kilian Weinberger -
2019 Oral: Emerging Convolutions for Generative Normalizing Flows »
Emiel Hoogeboom · Rianne Van den Berg · Max Welling -
2019 Poster: Simplifying Graph Convolutional Networks »
Felix Wu · Amauri Souza · Tianyi Zhang · Christopher Fifty · Tao Yu · Kilian Weinberger -
2019 Poster: Gauge Equivariant Convolutional Networks and the Icosahedral CNN »
Taco Cohen · Maurice Weiler · Berkay Kicanaoglu · Max Welling -
2019 Oral: Simplifying Graph Convolutional Networks »
Felix Wu · Amauri Souza · Tianyi Zhang · Christopher Fifty · Tao Yu · Kilian Weinberger -
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 Poster: Constant-Time Predictive Distributions for Gaussian Processes »
Geoff Pleiss · Jacob Gardner · Kilian Weinberger · Andrew Wilson -
2018 Oral: Attention-based Deep Multiple Instance Learning »
Maximilian Ilse · Jakub Tomczak · Max Welling -
2018 Oral: Constant-Time Predictive Distributions for Gaussian Processes »
Geoff Pleiss · Jacob Gardner · Kilian Weinberger · Andrew Wilson -
2018 Poster: Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning »
Thomas Dietterich · George Trimponias · Zhitang Chen -
2018 Poster: Open Category Detection with PAC Guarantees »
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks -
2018 Oral: Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning »
Thomas Dietterich · George Trimponias · Zhitang Chen -
2018 Oral: Open Category Detection with PAC Guarantees »
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks -
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 -
2017 Poster: On Calibration of Modern Neural Networks »
Chuan Guo · Geoff Pleiss · Yu Sun · Kilian Weinberger -
2017 Talk: On Calibration of Modern Neural Networks »
Chuan Guo · Geoff Pleiss · Yu Sun · Kilian Weinberger