More from the Same Authors

• 2021 : Understanding Post-hoc Adaptation for Improving Subgroup Robustness »
  David Madras · Richard Zemel
• 2021 : Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data »
  Sindy Löwe · David Madras · Richard Zemel · Max Welling
• 2022 Poster: Implications of Model Indeterminacy for Explanations of Automated Decisions »
  Marc-Etienne Brunet · Ashton Anderson · Richard Zemel
• 2022 Poster: Deep Ensembles Work, But Are They Necessary? »
  Taiga Abe · Estefany Kelly Buchanan · Geoff Pleiss · Richard Zemel · John Cunningham
• 2021 Poster: Variational Model Inversion Attacks »
  Kuan-Chieh Wang · YAN FU · Ke Li · Ashish Khisti · Richard Zemel · Alireza Makhzani
• 2021 Poster: Identifying and Benchmarking Natural Out-of-Context Prediction Problems »
  David Madras · Richard Zemel
• 2020 : Contributed talks 5: Fairness and Robustness in Invariant Learning: A Case Study in Toxicity Classification »
  Elliot Creager · David Madras · Richard Zemel
• 2019 Poster: Incremental Few-Shot Learning with Attention Attractor Networks »
  Mengye Ren · Renjie Liao · Ethan Fetaya · Richard Zemel
• 2019 Poster: SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies »
  Kamyar Ghasemipour · Shixiang (Shane) Gu · Richard Zemel
• 2019 Poster: Efficient Graph Generation with Graph Recurrent Attention Networks »
  Renjie Liao · Yujia Li · Yang Song · Shenlong Wang · Will Hamilton · David Duvenaud · Raquel Urtasun · Richard Zemel
• 2018 Poster: Learning Latent Subspaces in Variational Autoencoders »
  Jack Klys · Jake Snell · Richard Zemel
• 2018 Poster: Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer »
  David Madras · Toni Pitassi · Richard Zemel
• 2018 Poster: Neural Guided Constraint Logic Programming for Program Synthesis »
  Lisa Zhang · Gregory Rosenblatt · Ethan Fetaya · Renjie Liao · William Byrd · Matthew Might · Raquel Urtasun · Richard Zemel
• 2017 : Contributed talk: Predict Responsibly: Increasing Fairness by Learning To Defer Abstract »
  David Madras · Richard Zemel · Toni Pitassi
• 2017 Poster: Dualing GANs »
  Yujia Li · Alex Schwing · Kuan-Chieh Wang · Richard Zemel
• 2017 Poster: Causal Effect Inference with Deep Latent-Variable Models »
  Christos Louizos · Uri Shalit · Joris Mooij · David Sontag · Richard Zemel · Max Welling
• 2017 Spotlight: Dualing GANs »
  Yujia Li · Alex Schwing · Kuan-Chieh Wang · Richard Zemel
• 2017 Poster: Few-Shot Learning Through an Information Retrieval Lens »
  Eleni Triantafillou · Richard Zemel · Raquel Urtasun
• 2017 Poster: Prototypical Networks for Few-shot Learning »
  Jake Snell · Kevin Swersky · Richard Zemel
• 2016 Poster: Understanding the Effective Receptive Field in Deep Convolutional Neural Networks »
  Wenjie Luo · Yujia Li · Raquel Urtasun · Richard Zemel
• 2016 Poster: Learning Deep Parsimonious Representations »
  Renjie Liao · Alex Schwing · Richard Zemel · Raquel Urtasun
• 2015 Poster: Skip-Thought Vectors »
  Jamie Kiros · Yukun Zhu · Russ Salakhutdinov · Richard Zemel · Raquel Urtasun · Antonio Torralba · Sanja Fidler
• 2015 Poster: Exploring Models and Data for Image Question Answering »
  Mengye Ren · Jamie Kiros · Richard Zemel
• 2014 Workshop: Representation and Learning Methods for Complex Outputs »
  Richard Zemel · Dale Schuurmans · Kilian Q Weinberger · Yuhong Guo · Jia Deng · Francesco Dinuzzo · Hal Daumé III · Honglak Lee · Noah A Smith · Richard Sutton · Jiaqian YU · Vitaly Kuznetsov · Luke Vilnis · Hanchen Xiong · Calvin Murdock · Thomas Unterthiner · Jean-Francis Roy · Martin Renqiang Min · Hichem SAHBI · Fabio Massimo Zanzotto
• 2014 Poster: A Multiplicative Model for Learning Distributed Text-Based Attribute Representations »
  Jamie Kiros · Richard Zemel · Russ Salakhutdinov
• 2013 Workshop: Output Representation Learning »
  Yuhong Guo · Dale Schuurmans · Richard Zemel · Samy Bengio · Yoshua Bengio · Li Deng · Dan Roth · Kilian Q Weinberger · Jason Weston · Kihyuk Sohn · Florent Perronnin · Gabriel Synnaeve · Pablo R Strasser · julien audiffren · Carlo Ciliberto · Dan Goldwasser
• 2013 Poster: A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data »
  Jasper Snoek · Richard Zemel · Ryan Adams
• 2013 Poster: On the Expressive Power of Restricted Boltzmann Machines »
  James Martens · Arkadev Chattopadhya · Toni Pitassi · Richard Zemel
• 2012 Poster: Collaborative Ranking With 17 Parameters »
  Maksims Volkovs · Richard Zemel
• 2012 Poster: Bayesian n-Choose-k Models for Classification and Ranking »
  Kevin Swersky · Danny Tarlow · Richard Zemel · Ryan Adams · Brendan J Frey
• 2012 Poster: Efficient Sampling for Bipartite Matching Problems »
  Maksims Volkovs · Richard Zemel
• 2012 Poster: Cardinality Restricted Boltzmann Machines »
  Kevin Swersky · Danny Tarlow · Ilya Sutskever · Richard Zemel · Russ Salakhutdinov · Ryan Adams
• 2010 Talk: Opening Remarks and Awards »
  Richard Zemel · Terrence Sejnowski · John Shawe-Taylor
• 2008 Poster: Comparing model predictions of response bias and variance in cue combination »
  Rama Natarajan · Iain Murray · Ladan Shams · Richard Zemel
• 2008 Poster: Learning Hybrid Models for Image Annotation with Partially Labeled Data »
  Xuming He · Richard Zemel
• 2008 Poster: Competing RBM density models for classification of fMRI images »
  Tanya Schmah · Geoffrey E Hinton · Richard Zemel