More from the Same Authors

• 2022 Poster: On Implicit Bias in Overparameterized Bilevel Optimization »
  Paul Vicol · Jonathan Lorraine · Fabian Pedregosa · David Duvenaud · Roger Grosse
• 2022 Spotlight: On Implicit Bias in Overparameterized Bilevel Optimization »
  Paul Vicol · Jonathan Lorraine · Fabian Pedregosa · David Duvenaud · Roger Grosse
• 2021 Poster: Oops I Took A Gradient: Scalable Sampling for Discrete Distributions »
  Will Grathwohl · Kevin Swersky · Milad Hashemi · David Duvenaud · Chris Maddison
• 2021 Oral: Oops I Took A Gradient: Scalable Sampling for Discrete Distributions »
  Will Grathwohl · Kevin Swersky · Milad Hashemi · David Duvenaud · Chris Maddison
• 2020 Poster: Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling »
  Will Grathwohl · Kuan-Chieh Wang · Joern-Henrik Jacobsen · David Duvenaud · Richard Zemel
• 2019 Poster: Invertible Residual Networks »
  Jens Behrmann · Will Grathwohl · Ricky T. Q. Chen · David Duvenaud · Joern-Henrik Jacobsen
• 2019 Oral: Invertible Residual Networks »
  Jens Behrmann · Will Grathwohl · Ricky T. Q. Chen · David Duvenaud · Joern-Henrik Jacobsen
• 2018 Poster: Noisy Natural Gradient as Variational Inference »
  Guodong Zhang · Shengyang Sun · David Duvenaud · Roger Grosse
• 2018 Oral: Noisy Natural Gradient as Variational Inference »
  Guodong Zhang · Shengyang Sun · David Duvenaud · Roger Grosse
• 2018 Poster: Inference Suboptimality in Variational Autoencoders »
  Chris Cremer · Xuechen Li · David Duvenaud
• 2018 Oral: Inference Suboptimality in Variational Autoencoders »
  Chris Cremer · Xuechen Li · David Duvenaud