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Frank Wood

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Papers (44)

  1. Discrete Meanflow Training Curriculum cs.LG · 2026 · author #2
  2. The Virtual Patch Clamp: Imputing C. elegans Membrane Potentials from Calcium Imaging q-bio.NC · 2019 · author #3
  3. Amortized Monte Carlo Integration stat.ML · 2019 · author #2
  4. LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models cs.LG · 2019 · author #6
  5. Inference Trees: Adaptive Inference with Exploration stat.CO · 2018 · author #5
  6. Deep Variational Reinforcement Learning for POMDPs cs.LG · 2018 · author #4
  7. Hamiltonian Monte Carlo for Probabilistic Programs with Discontinuities stat.CO · 2018 · author #6
  8. High Throughput Synchronous Distributed Stochastic Gradient Descent cs.DC · 2018 · author #2
  9. Tighter Variational Bounds are Not Necessarily Better stat.ML · 2018 · author #6
  10. Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators cs.AI · 2017 · author #5
  11. Faithful Inversion of Generative Models for Effective Amortized Inference stat.ML · 2017 · author #7
  12. Updating the VESICLE-CNN Synapse Detector cs.CV · 2017 · author #2
  13. On Nesting Monte Carlo Estimators stat.CO · 2017 · author #5
  14. Bayesian Optimization for Probabilistic Programs stat.ML · 2017 · author #5
  15. Learning Disentangled Representations with Semi-Supervised Deep Generative Models stat.ML · 2017 · author #7
  16. Auto-Encoding Sequential Monte Carlo stat.ML · 2017 · author #5
  17. Online Learning Rate Adaptation with Hypergradient Descent cs.LG · 2017 · author #5
  18. Using Synthetic Data to Train Neural Networks is Model-Based Reasoning cs.LG · 2017 · author #4
  19. On the Pitfalls of Nested Monte Carlo stat.CO · 2016 · author #4
  20. Inducing Interpretable Representations with Variational Autoencoders stat.ML · 2016 · author #5
  21. Probabilistic structure discovery in time series data stat.ML · 2016 · author #5
  22. Inference Compilation and Universal Probabilistic Programming cs.AI · 2016 · author #3
  23. Design and Implementation of Probabilistic Programming Language Anglican cs.PL · 2016 · author #4
  24. Spreadsheet Probabilistic Programming cs.AI · 2016 · author #3
  25. Inference Networks for Sequential Monte Carlo in Graphical Models stat.ML · 2016 · author #2
  26. Interacting Particle Markov Chain Monte Carlo stat.CO · 2016 · author #7
  27. Semantics for probabilistic programming: higher-order functions, continuous distributions, and soft constraints cs.PL · 2016 · author #5
  28. Data-driven Sequential Monte Carlo in Probabilistic Programming cs.AI · 2015 · author #3
  29. Canonical Correlation Forests stat.ML · 2015 · author #2
  30. Black-Box Policy Search with Probabilistic Programs stat.ML · 2015 · author #4
  31. A New Approach to Probabilistic Programming Inference stat.ML · 2015 · author #1
  32. Maximum a Posteriori Estimation by Search in Probabilistic Programs cs.AI · 2015 · author #2
  33. Path Finding under Uncertainty through Probabilistic Inference cs.AI · 2015 · author #4
  34. Particle Gibbs with Ancestor Sampling for Probabilistic Programs stat.ML · 2015 · author #4
  35. Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs cs.AI · 2015 · author #4
  36. Asynchronous Anytime Sequential Monte Carlo stat.CO · 2014 · author #2
  37. Infinite Structured Hidden Semi-Markov Models stat.ME · 2014 · author #2
  38. A Compilation Target for Probabilistic Programming Languages cs.AI · 2014 · author #2
  39. Tempering by Subsampling stat.ML · 2014 · author #3
  40. Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data stat.ML · 2013 · author #3
  41. Inferring Team Strengths Using a Discrete Markov Random Field stat.ML · 2013 · author #2
  42. Unsupervised Detection and Tracking of Arbitrary Objects with Dependent Dirichlet Process Mixtures stat.ML · 2012 · author #2
  43. A Non-Parametric Bayesian Method for Inferring Hidden Causes cs.LG · 2012 · author #1
  44. Inference in Hidden Markov Models with Explicit State Duration Distributions stat.ML · 2012 · author #3

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