David Duvenaud
29 papers · 2013–2025 · 5 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 9 separate collaboration groups - the largest holds only 41% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which David Duvenaud?
5 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Will Grathwohl, Ricky T. Q. Chen, Mohammad Norouzi
12 papers
· 2018–2024
· ICLR, ICML, AISTATS
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LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language
NeurIPS 2024
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations
AISTATS 2022
No MCMC for me: Amortized sampling for fast and stable training of energy-based models
ICLR 2021
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
ICML 2021
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
ICML 2020
SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models
ICLR 2020
Scalable Gradients for Stochastic Differential Equations
AISTATS 2020
Your classifier is secretly an energy based model and you should treat it like one
ICLR 2020
FFJORD: Free-Form Continuous Dynamics for Scalable Reversible Generative Models
ICLR 2019
Invertible Residual Networks
ICML 2019
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation
ICLR 2018
Inference Suboptimality in Variational Autoencoders
ICML 2018