More from the Same Authors

• 2021 : Multi-Group Reinforcement Learning for Maternal Health in Childbirth »
  Barbara Engelhardt · Promise Ekpo
• 2022 : Multi-fidelity Bayesian experimental design using power posteriors »
  Andrew Jones · Diana Cai · Barbara Engelhardt
• 2022 : Sequential Gaussian Processes for Online Learning of Nonstationary Functions »
  Michael Minyi Zhang · Bianca Dumitrascu · Sinead Williamson · Barbara Engelhardt
• 2022 : Detecting Synthetic Opioids with NQR Spectroscopy and Complex-Valued Signal Denoising »
  Amber Day · Natalie Klein · Michael Malone · Harris Mason · Sinead Williamson
• 2022 : Detecting State Changes in Dynamic Neuronal Networks »
  Yiwei Gong · Sinead Williamson
• 2022 : Multi-group Reinforcement Learning for Electrolyte Repletion »
  Promise Ekpo · Barbara Engelhardt
• 2022 : Spike-and-Slab Probabilistic Backpropagation: When Smarter Approximations Make No Difference »
  Evan Ott · Sinead Williamson
• 2021 : Invited talk (ML) - Barbara Engelhardt »
  Barbara Engelhardt
• 2021 Workshop: Your Model is Wrong: Robustness and misspecification in probabilistic modeling »
  Diana Cai · Sameer Deshpande · Michael Hughes · Tamara Broderick · Trevor Campbell · Nick Foti · Barbara Engelhardt · Sinead Williamson
• 2021 Workshop: Learning Meaningful Representations of Life (LMRL) »
  Elizabeth Wood · Adji Bousso Dieng · Aleksandrina Goeva · Anshul Kundaje · Barbara Engelhardt · Chang Liu · David Van Valen · Debora Marks · Edward Boyden · Eli N Weinstein · Lorin Crawford · Mor Nitzan · Romain Lopez · Tamara Broderick · Ray Jones · Wouter Boomsma · Yixin Wang
• 2021 Panel: How Should a Machine Learning Researcher Think About AI Ethics? »
  Amanda Askell · Abeba Birhane · Jesse Dodge · Casey Fiesler · Pascale N Fung · Hanna Wallach
• 2020 : Panel & Closing »
  Tamara Broderick · Laurent Dinh · Neil Lawrence · Kristian Lum · Hanna Wallach · Sinead Williamson
• 2020 : Morning keynote »
  Hanna Wallach · Rosie Campbell
• 2020 Workshop: I Can’t Believe It’s Not Better! Bridging the gap between theory and empiricism in probabilistic machine learning »
  Jessica Forde · Francisco Ruiz · Melanie Fernandez Pradier · Aaron Schein · Finale Doshi-Velez · Isabel Valera · David Blei · Hanna Wallach
• 2019 : In conversations: Daphne Koller and Barbara Englehardt »
  Daphne Koller · Barbara Engelhardt
• 2019 Workshop: Learning Meaningful Representations of Life »
  Elizabeth Wood · Yakir Reshef · Jonathan Bloom · Jasper Snoek · Barbara Engelhardt · Scott Linderman · Suchi Saria · Alexander Wiltschko · Casey Greene · Chang Liu · Kresten Lindorff-Larsen · Debora Marks
• 2019 Poster: Poisson-Randomized Gamma Dynamical Systems »
  Aaron Schein · Scott Linderman · Mingyuan Zhou · David Blei · Hanna Wallach
• 2018 : Barbara Engelhardt »
  Barbara Engelhardt
• 2018 : Panel on research process »
  Zachary Lipton · Charles Sutton · Finale Doshi-Velez · Hanna Wallach · Suchi Saria · Rich Caruana · Thomas Rainforth
• 2018 : Hanna Wallach - Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? »
  Hanna Wallach
• 2018 Workshop: All of Bayesian Nonparametrics (Especially the Useful Bits) »
  Diana Cai · Trevor Campbell · Michael Hughes · Tamara Broderick · Nick Foti · Sinead Williamson
• 2017 : Neil Lawrence, Francis Bach and François Laviolette »
  Neil Lawrence · Francis Bach · Francois Laviolette
• 2017 : Panel Session »
  Neil Lawrence · Finale Doshi-Velez · Zoubin Ghahramani · Yann LeCun · Max Welling · Yee Whye Teh · Ole Winther
• 2017 : Revealing human inductive biases and metacognitive processes with rational models »
  Tom Griffiths
• 2017 : Poster spotlights »
  Hiroshi Kuwajima · Masayuki Tanaka · Qingkai Liang · Matthieu Komorowski · Fanyu Que · Thalita F Drumond · Aniruddh Raghu · Leo Anthony Celi · Christina Göpfert · Andrew Ross · Sarah Tan · Rich Caruana · Yin Lou · Devinder Kumar · Graham Taylor · Forough Poursabzi-Sangdeh · Jennifer Wortman Vaughan · Hanna Wallach
• 2017 Poster: A graph-theoretic approach to multitasking »
  Noga Alon · Daniel Reichman · Igor Shinkar · Tal Wagner · Sebastian Musslick · Jonathan D Cohen · Tom Griffiths · Biswadip dey · Kayhan Ozcimder
• 2017 Oral: A graph-theoretic approach to multitasking »
  Noga Alon · Daniel Reichman · Igor Shinkar · Tal Wagner · Sebastian Musslick · Jonathan D Cohen · Tom Griffiths · Biswadip dey · Kayhan Ozcimder
• 2016 Workshop: Machine Learning in Computational Biology »
  Gerald Quon · Sara Mostafavi · James Y Zou · Barbara Engelhardt · Oliver Stegle · Nicolo Fusi
• 2016 : Bounded Optimality and Rational Metareasoning in Human Cognition »
  Tom Griffiths
• 2016 Poster: Variance Reduction in Stochastic Gradient Langevin Dynamics »
  Kumar Avinava Dubey · Sashank J. Reddi · Sinead Williamson · Barnabas Poczos · Alexander Smola · Eric Xing
• 2016 Poster: Poisson-Gamma dynamical systems »
  Aaron Schein · Hanna Wallach · Mingyuan Zhou
• 2016 Oral: Poisson-Gamma dynamical systems »
  Aaron Schein · Hanna Wallach · Mingyuan Zhou
• 2016 Poster: Flexible Models for Microclustering with Application to Entity Resolution »
  Brenda Betancourt · Giacomo Zanella · Jeffrey Miller · Hanna Wallach · Abbas Zaidi · Beka Steorts
• 2015 Workshop: Bayesian Nonparametrics: The Next Generation »
  Tamara Broderick · Nick Foti · Aaron Schein · Alex Tank · Hanna Wallach · Sinead Williamson
• 2015 Workshop: Advances in Approximate Bayesian Inference »
  Dustin Tran · Tamara Broderick · Stephan Mandt · James McInerney · Shakir Mohamed · Alp Kucukelbir · Matthew D. Hoffman · Neil Lawrence · David Blei
• 2015 Workshop: Bounded Optimality and Rational Metareasoning »
  Samuel J Gershman · Falk Lieder · Tom Griffiths · Noah Goodman
• 2014 Poster: Algorithm selection by rational metareasoning as a model of human strategy selection »
  Falk Lieder · Dillon Plunkett · Jessica B Hamrick · Stuart J Russell · Nicholas Hay · Tom Griffiths
• 2014 Poster: Dependent nonparametric trees for dynamic hierarchical clustering »
  Kumar Avinava Dubey · Qirong Ho · Sinead Williamson · Eric Xing
• 2013 Workshop: Topic Models: Computation, Application, and Evaluation »
  David Mimno · Amr Ahmed · Jordan Boyd-Graber · Ankur Moitra · Hanna Wallach · Alexander Smola · David Blei · Anima Anandkumar
• 2013 Poster: Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies »
  Yangqing Jia · Joshua T Abbott · Joseph L Austerweil · Tom Griffiths · Trevor Darrell
• 2012 Poster: Topic-Partitioned Multinetwork Embeddings »
  Peter Krafft · Juston S Moore · Hanna Wallach · Bruce Desmarais
• 2012 Poster: Human memory search as a random walk in a semantic network »
  Joshua T Abbott · Joseph L Austerweil · Tom Griffiths
• 2012 Spotlight: Human memory search as a random walk in a semantic network »
  Joshua T Abbott · Joseph L Austerweil · Tom Griffiths
• 2012 Poster: Burn-in, bias, and the rationality of anchoring »
  Falk Lieder · Tom Griffiths · Noah Goodman
• 2011 Workshop: 2nd Workshop on Computational Social Science and the Wisdom of Crowds »
  Winter Mason · Jennifer Wortman Vaughan · Hanna Wallach
• 2011 Poster: A rational model of causal inference with continuous causes »
  M Pacer · Tom Griffiths
• 2011 Poster: An ideal observer model for identifying the reference frame of objects »
  Joseph L Austerweil · Abram Friesen · Tom Griffiths
• 2011 Poster: Testing a Bayesian Measure of Representativeness Using a Large Image Database »
  Joshua T Abbott · Katherine Heller · Zoubin Ghahramani · Tom Griffiths
• 2010 Workshop: Transfer Learning Via Rich Generative Models. »
  Russ Salakhutdinov · Ryan Adams · Josh Tenenbaum · Zoubin Ghahramani · Tom Griffiths
• 2010 Workshop: Computational Social Science and the Wisdom of Crowds »
  Jennifer Wortman Vaughan · Hanna Wallach
• 2010 Spotlight: Learning invariant features using the Transformed Indian Buffet Process »
  Joseph L Austerweil · Tom Griffiths
• 2010 Poster: Learning invariant features using the Transformed Indian Buffet Process »
  Joseph L Austerweil · Tom Griffiths
• 2009 Workshop: Bounded-rational analyses of human cognition: Bayesian models, approximate inference, and the brain »
  Noah Goodman · Edward Vul · Tom Griffiths · Josh Tenenbaum
• 2009 Workshop: Applications for Topic Models: Text and Beyond »
  David Blei · Jordan Boyd-Graber · Jonathan Chang · Katherine Heller · Hanna Wallach
• 2009 Poster: Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling »
  Lei ShiUpdateMe · Tom Griffiths
• 2009 Spotlight: Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling »
  Lei ShiUpdateMe · Tom Griffiths
• 2009 Poster: Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning »
  Anne Hsu · Tom Griffiths
• 2009 Oral: Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning »
  Anne Hsu · Tom Griffiths
• 2009 Poster: Rethinking LDA: Why Priors Matter »
  Hanna Wallach · David Mimno · Andrew McCallum
• 2009 Poster: Nonparametric Latent Feature Models for Link Prediction »
  Kurt T Miller · Tom Griffiths · Michael Jordan
• 2009 Spotlight: Nonparametric Latent Feature Models for Link Prediction »
  Kurt T Miller · Tom Griffiths · Michael Jordan
• 2009 Spotlight: Rethinking LDA: Why Priors Matter »
  Hanna Wallach · David Mimno · Andrew McCallum
• 2008 Workshop: Machine learning meets human learning »
  Nathaniel D Daw · Tom Griffiths · Josh Tenenbaum · Jerry Zhu
• 2008 Poster: Modeling the effects of memory on human online sentence processing with particle filters »
  Roger Levy · Florencia Reali · Tom Griffiths
• 2008 Oral: Modeling the effects of memory on human online sentence processing with particle filters »
  Roger Levy · Florencia Reali · Tom Griffiths
• 2008 Poster: How memory biases affect information transmission: A rational analysis of serial reproduction »
  Jing Xu · Tom Griffiths
• 2008 Poster: Analyzing human feature learning as nonparametric Bayesian inference »
  Joseph L Austerweil · Tom Griffiths
• 2008 Poster: A rational model of preference learning and choice prediction by children »
  Chris Lucas · Tom Griffiths · Fei Xu · Christine Fawcett
• 2008 Spotlight: Analyzing human feature learning as nonparametric Bayesian inference »
  Joseph L Austerweil · Tom Griffiths
• 2008 Spotlight: A rational model of preference learning and choice prediction by children »
  Chris Lucas · Tom Griffiths · Fei Xu · Christine Fawcett
• 2008 Spotlight: How memory biases affect information transmission: A rational analysis of serial reproduction »
  Jing Xu · Tom Griffiths
• 2008 Poster: Modeling human function learning with Gaussian processes »
  Tom Griffiths · Chris Lucas · Joseph Jay Williams · Michael Kalish
• 2007 Oral: Markov Chain Monte Carlo with People »
  Adam Sanborn · Tom Griffiths
• 2007 Poster: Markov Chain Monte Carlo with People »
  Adam Sanborn · Tom Griffiths
• 2007 Poster: A Probabilistic Approach to Language Change »
  Alexandre Bouchard-Côté · Percy Liang · Tom Griffiths · Dan Klein
• 2006 Poster: Particle Filtering for Nonparametric Bayesian Matrix Factorization »
  Frank Wood · Tom Griffiths
• 2006 Poster: Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Mod »
  Mark Johnson · Tom Griffiths · Sharon Goldwater
• 2006 Poster: A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments »
  Daniel Navarro · Tom Griffiths