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Live Panel
Max Welling · Bharath Ramsundar · Irina Rish · Karianne J Bergen · Pushmeet Kohli
Author Information
Max Welling (University of Amsterdam / Qualcomm AI Research)
Bharath Ramsundar (DeepChem)
Irina Rish (MILA / Université de Montréal)
Karianne J Bergen (Brown University)
Pushmeet Kohli (DeepMind)
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2021 Spotlight: Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization »
Kartik Ahuja · Ethan Caballero · Dinghuai Zhang · Jean-Christophe Gagnon-Audet · Yoshua Bengio · Ioannis Mitliagkas · Irina Rish -
2021 : Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs »
Dan Rosenbaum · Marta Garnelo · Michal Zielinski · Charles Beattie · Ellen Clancy · Andrea Huber · Pushmeet Kohli · Andrew Senior · John Jumper · Carl Doersch · S. M. Ali Eslami · Olaf Ronneberger · Jonas Adler -
2021 : Bringing Atomistic Deep Learning to Prime Time »
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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 -
2022 Spotlight: Alleviating Adversarial Attacks on Variational Autoencoders with MCMC »
Anna Kuzina · Max Welling · Jakub Tomczak -
2022 : Panel »
Jeevana Priya Inala · Pushmeet Kohli · Ann Kennedy · Sriram Rajamani · Yisong Yue -
2022 : Invited Speaker »
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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 -
2022 Poster: Continual Learning In Environments With Polynomial Mixing Times »
Matthew Riemer · Sharath Chandra Raparthy · Ignacio Cases · Gopeshh Subbaraj · Maximilian Puelma Touzel · Irina Rish -
2021 : Continual Learning In Environments With Polynomial Mixing Times »
Matthew Riemer · Sharath Chandra Raparthy · Ignacio Cases · Gopeshh Subbaraj · Maximilian Puelma Touzel · Irina Rish -
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 : Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs »
Dan Rosenbaum · Marta Garnelo · Michal Zielinski · Charles Beattie · Ellen Clancy · Andrea Huber · Pushmeet Kohli · Andrew Senior · John Jumper · Carl Doersch · S. M. Ali Eslami · Olaf Ronneberger · Jonas Adler -
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: Adversarial Feature Desensitization »
Pouya Bashivan · Reza Bayat · Adam Ibrahim · Kartik Ahuja · Mojtaba Faramarzi · Touraj Laleh · Blake Richards · Irina Rish -
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: Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization »
Kartik Ahuja · Ethan Caballero · Dinghuai Zhang · Jean-Christophe Gagnon-Audet · Yoshua Bengio · Ioannis Mitliagkas · Irina Rish -
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 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 -
2020 Poster: Training Generative Adversarial Networks by Solving Ordinary Differential Equations »
Chongli Qin · Yan Wu · Jost Tobias Springenberg · Andy Brock · Jeff Donahue · Timothy Lillicrap · Pushmeet Kohli -
2020 Poster: Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming »
Sumanth Dathathri · Krishnamurthy Dvijotham · Alexey Kurakin · Aditi Raghunathan · Jonathan Uesato · Rudy Bunel · Shreya Shankar · Jacob Steinhardt · Ian Goodfellow · Percy Liang · Pushmeet Kohli -
2020 Spotlight: Training Generative Adversarial Networks by Solving Ordinary Differential Equations »
Chongli Qin · Yan Wu · Jost Tobias Springenberg · Andy Brock · Jeff Donahue · Timothy Lillicrap · Pushmeet Kohli -
2020 Poster: The Autoencoding Variational Autoencoder »
Taylan Cemgil · Sumedh Ghaisas · Krishnamurthy Dvijotham · Sven Gowal · Pushmeet Kohli -
2020 Spotlight: The Autoencoding Variational Autoencoder »
Taylan Cemgil · Sumedh Ghaisas · Krishnamurthy Dvijotham · Sven Gowal · Pushmeet Kohli -
2019 : Poster Session »
Pravish Sainath · Mohamed Akrout · Charles Delahunt · Nathan Kutz · Guangyu Robert Yang · Joseph Marino · L F Abbott · Nicolas Vecoven · Damien Ernst · andrew warrington · Michael Kagan · Kyunghyun Cho · Kameron Harris · Leopold Grinberg · John J. Hopfield · Dmitry Krotov · Taliah Muhammad · Erick Cobos · Edgar Walker · Jacob Reimer · Andreas Tolias · Alexander Ecker · Janaki Sheth · Yu Zhang · Maciej Wołczyk · Jacek Tabor · Szymon Maszke · Roman Pogodin · Dane Corneil · Wulfram Gerstner · Baihan Lin · Guillermo Cecchi · Jenna M Reinen · Irina Rish · Guillaume Bellec · Darjan Salaj · Anand Subramoney · Wolfgang Maass · Yueqi Wang · Ari Pakman · Jin Hyung Lee · Liam Paninski · Bryan Tripp · Colin Graber · Alex Schwing · Luke Prince · Gabriel Ocker · Michael Buice · Benjamin Lansdell · Konrad Kording · Jack Lindsey · Terrence Sejnowski · Matthew Farrell · Eric Shea-Brown · Nicolas Farrugia · Victor Nepveu · Jiwoong Im · Kristin Branson · Brian Hu · Ramakrishnan Iyer · Stefan Mihalas · Sneha Aenugu · Hananel Hazan · Sihui Dai · Tan Nguyen · Doris Tsao · Richard Baraniuk · Anima Anandkumar · Hidenori Tanaka · Aran Nayebi · Stephen Baccus · Surya Ganguli · Dean Pospisil · Eilif Muller · Jeffrey S Cheng · Gaël Varoquaux · Kamalaker Dadi · Dimitrios C Gklezakos · Rajesh PN Rao · Anand Louis · Christos Papadimitriou · Santosh Vempala · Naganand Yadati · Daniel Zdeblick · Daniela M Witten · Nicholas Roberts · Vinay Prabhu · Pierre Bellec · Poornima Ramesh · Jakob H Macke · Santiago Cadena · Guillaume Bellec · Franz Scherr · Owen Marschall · Robert Kim · Hannes Rapp · Marcio Fonseca · Oliver Armitage · Jiwoong Im · Thomas Hardcastle · Abhishek Sharma · Wyeth Bair · Adrian Valente · Shane Shang · Merav Stern · Rutuja Patil · Peter Wang · Sruthi Gorantla · Peter Stratton · Tristan Edwards · Jialin Lu · Martin Ester · Yurii Vlasov · Siavash Golkar -
2019 : TBD »
Max Welling -
2019 : Coffee Break & Poster Session »
Samia Mohinta · Andrea Agostinelli · Alexandra Moringen · Jee Hang Lee · Yat Long Lo · Wolfgang Maass · Blue Sheffer · Colin Bredenberg · Benjamin Eysenbach · Liyu Xia · Efstratios Markou · Jan Lichtenberg · Pierre Richemond · Tony Zhang · JB Lanier · Baihan Lin · William Fedus · Glen Berseth · Marta Sarrico · Matthew Crosby · Stephen McAleer · Sina Ghiassian · Franz Scherr · Guillaume Bellec · Darjan Salaj · Arinbjörn Kolbeinsson · Matthew Rosenberg · Jaehoon Shin · Sang Wan Lee · Guillermo Cecchi · Irina Rish · Elias Hajek -
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: Learning Transferable Graph Exploration »
Hanjun Dai · Yujia Li · Chenglong Wang · Rishabh Singh · Po-Sen Huang · Pushmeet Kohli -
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: Are Labels Required for Improving Adversarial Robustness? »
Jean-Baptiste Alayrac · Jonathan Uesato · Po-Sen Huang · Alhussein Fawzi · Robert Stanforth · Pushmeet Kohli -
2019 Poster: Adversarial Robustness through Local Linearization »
Chongli Qin · James Martens · Sven Gowal · Dilip Krishnan · Krishnamurthy Dvijotham · Alhussein Fawzi · Soham De · Robert Stanforth · Pushmeet Kohli -
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 »
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: A Unified View of Piecewise Linear Neural Network Verification »
Rudy Bunel · Ilker Turkaslan · Philip Torr · Pushmeet Kohli · Pawan K Mudigonda -
2018 Poster: Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding »
Kexin Yi · Jiajun Wu · Chuang Gan · Antonio Torralba · Pushmeet Kohli · Josh Tenenbaum -
2018 Spotlight: Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding »
Kexin Yi · Jiajun Wu · Chuang Gan · Antonio Torralba · Pushmeet Kohli · Josh Tenenbaum -
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 : Deep Bayes for Distributed Learning, Uncertainty Quantification and Compression »
Max Welling -
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 Workshop: Representation Learning in Artificial and Biological Neural Networks »
Leila Wehbe · Marcel Van Gerven · Moritz Grosse-Wentrup · Irina Rish · Brian Murphy · Georg Langs · Guillermo Cecchi · Anwar O Nunez-Elizalde -
2016 Invited Talk: Learning About the Brain: Neuroimaging and Beyond »
Irina Rish -
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 Workshop: Machine Learning and Interpretation in Neuroimaging (day 1) »
Irina Rish · Leila Wehbe · Brian Murphy · Georg Langs · Guillermo Cecchi · Moritz Grosse-Wentrup -
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: MLINI 2014 - 4th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging: Beyond the Scanner »
Irina Rish · Georg Langs · Brian Murphy · Guillermo Cecchi · Kai-min K Chang · Leila Wehbe -
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: MLINI-13: Machine Learning and Interpretation in Neuroimaging (Day 2) »
Georg Langs · Brian Murphy · Kai-min K Chang · Paolo Avesani · James Haxby · Nikolaus Kriegeskorte · Susan Whitfield-Gabrieli · Irina Rish · Guillermo Cecchi · Raif Rustamov · Marius Kloft · Jonathan Young · Sina Ghiassian · Michael Coen -
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 -
2013 Workshop: MLINI-13: Machine Learning and Interpretation in Neuroimaging (Day 1) »
Georg Langs · Brian Murphy · Kai-min K Chang · Paolo Avesani · James Haxby · Nikolaus Kriegeskorte · Susan Whitfield-Gabrieli · Irina Rish · Guillermo Cecchi · Raif Rustamov · Marius Kloft · Jonathan Young · Sina Ghiassian · Michael Coen -
2012 Workshop: MLINI - 2nd NIPS Workshop on Machine Learning and Interpretation in Neuroimaging (2 day) »
Georg Langs · Irina Rish · Guillermo Cecchi · Brian Murphy · Bjoern Menze · Kai-min K Chang · Moritz Grosse-Wentrup -
2012 Workshop: MLINI - 2nd NIPS Workshop on Machine Learning and Interpretation in Neuroimaging (2 day) »
Georg Langs · Irina Rish · Guillermo Cecchi · Brian Murphy · Bjoern Menze · Kai-min K Chang · Moritz Grosse-Wentrup -
2012 Poster: The Time-Marginalized Coalescent Prior for Hierarchical Clustering »
Levi Boyles · Max Welling -
2011 Workshop: Machine Learning and Interpretation in Neuroimaging (MLINI-2011) »
Melissa K Carroll · Guillermo Cecchi · Kai-min K Chang · Moritz Grosse-Wentrup · James Haxby · Georg Langs · Anna Korhonen · Bjoern Menze · Brian Murphy · Janaina Mourao-Miranda · Vittorio Murino · Francisco Pereira · Irina Rish · Mert Sabuncu · Irina Simanova · Bertrand Thirion -
2011 Poster: Statistical Tests for Optimization Efficiency »
Levi Boyles · Anoop Korattikara · Deva Ramanan · Max Welling -
2010 Workshop: Practical Application of Sparse Modeling: Open Issues and New Directions »
Irina Rish · Alexandru Niculescu-Mizil · Guillermo Cecchi · Aurelie Lozano -
2010 Session: Spotlights Session 12 »
Irina Rish -
2010 Session: Oral Session 15 »
Irina Rish -
2010 Poster: On Herding and the Perceptron Cycling Theorem »
Andrew E Gelfand · Yutian Chen · Laurens van der Maaten · Max Welling -
2009 Poster: Discriminative Network Models of Schizophrenia »
Guillermo Cecchi · Irina Rish · Benjamin Thyreau · Bertrand Thirion · Marion Plaze · Jean-Luc Martinot · Marie Laure Paillere-Martinot · Jean-Baptiste Poline -
2009 Oral: Discriminative Network Models of Schizophrenia »
Guillermo Cecchi · Irina Rish · Benjamin Thyreau · Bertrand Thirion · Marion Plaze · Jean-Luc Martinot · Marie Laure Paillere-Martinot · Jean-Baptiste Poline -
2008 Workshop: New Directions in Statistical Learning for Meaningful and Reproducible fMRI Analysis »
Melissa K Carroll · Irina Rish · Francisco Pereira · Guillermo Cecchi -
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 Workshop: Novel Applications of Dimensionality Reduction »
John Blitzer · Rajarshi Das · Irina Rish · Kilian Q Weinberger -
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