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Frank Wood

Identifiers

  • name variant Frank Wood 0.60 · backfill

Papers (45)

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

Mentions

  • 1305.3640 #3 · backfill · confidence 0.70 Frank Wood
  • 1305.1998 #2 · backfill · confidence 0.70 Frank Wood
  • 2605.24192 #3 · arxiv_oai · confidence 0.70 Frank Wood
  • 1210.3288 #2 · backfill · confidence 0.70 Frank Wood
  • 1206.6865 #1 · backfill · confidence 0.70 Frank Wood
  • 1203.0038 #3 · backfill · confidence 0.70 Frank Wood

Frequent Coauthors