Frank Wood
Identifiers
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Papers (44)
- Discrete Meanflow Training Curriculum cs.LG · 2026 · author #2
- The Virtual Patch Clamp: Imputing C. elegans Membrane Potentials from Calcium Imaging q-bio.NC · 2019 · author #3
- Amortized Monte Carlo Integration stat.ML · 2019 · author #2
- LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models cs.LG · 2019 · author #6
- Inference Trees: Adaptive Inference with Exploration stat.CO · 2018 · author #5
- Deep Variational Reinforcement Learning for POMDPs cs.LG · 2018 · author #4
- Hamiltonian Monte Carlo for Probabilistic Programs with Discontinuities stat.CO · 2018 · author #6
- High Throughput Synchronous Distributed Stochastic Gradient Descent cs.DC · 2018 · author #2
- Tighter Variational Bounds are Not Necessarily Better stat.ML · 2018 · author #6
- Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators cs.AI · 2017 · author #5
- Faithful Inversion of Generative Models for Effective Amortized Inference stat.ML · 2017 · author #7
- Updating the VESICLE-CNN Synapse Detector cs.CV · 2017 · author #2
- On Nesting Monte Carlo Estimators stat.CO · 2017 · author #5
- Bayesian Optimization for Probabilistic Programs stat.ML · 2017 · author #5
- Learning Disentangled Representations with Semi-Supervised Deep Generative Models stat.ML · 2017 · author #7
- Auto-Encoding Sequential Monte Carlo stat.ML · 2017 · author #5
- Online Learning Rate Adaptation with Hypergradient Descent cs.LG · 2017 · author #5
- Using Synthetic Data to Train Neural Networks is Model-Based Reasoning cs.LG · 2017 · author #4
- On the Pitfalls of Nested Monte Carlo stat.CO · 2016 · author #4
- Inducing Interpretable Representations with Variational Autoencoders stat.ML · 2016 · author #5
- Probabilistic structure discovery in time series data stat.ML · 2016 · author #5
- Inference Compilation and Universal Probabilistic Programming cs.AI · 2016 · author #3
- Design and Implementation of Probabilistic Programming Language Anglican cs.PL · 2016 · author #4
- Spreadsheet Probabilistic Programming cs.AI · 2016 · author #3
- Inference Networks for Sequential Monte Carlo in Graphical Models stat.ML · 2016 · author #2
- Interacting Particle Markov Chain Monte Carlo stat.CO · 2016 · author #7
- Semantics for probabilistic programming: higher-order functions, continuous distributions, and soft constraints cs.PL · 2016 · author #5
- Data-driven Sequential Monte Carlo in Probabilistic Programming cs.AI · 2015 · author #3
- Canonical Correlation Forests stat.ML · 2015 · author #2
- Black-Box Policy Search with Probabilistic Programs stat.ML · 2015 · author #4
- A New Approach to Probabilistic Programming Inference stat.ML · 2015 · author #1
- Maximum a Posteriori Estimation by Search in Probabilistic Programs cs.AI · 2015 · author #2
- Path Finding under Uncertainty through Probabilistic Inference cs.AI · 2015 · author #4
- Particle Gibbs with Ancestor Sampling for Probabilistic Programs stat.ML · 2015 · author #4
- Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs cs.AI · 2015 · author #4
- Asynchronous Anytime Sequential Monte Carlo stat.CO · 2014 · author #2
- Infinite Structured Hidden Semi-Markov Models stat.ME · 2014 · author #2
- A Compilation Target for Probabilistic Programming Languages cs.AI · 2014 · author #2
- Tempering by Subsampling stat.ML · 2014 · author #3
- Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data stat.ML · 2013 · author #3
- Inferring Team Strengths Using a Discrete Markov Random Field stat.ML · 2013 · author #2
- Unsupervised Detection and Tracking of Arbitrary Objects with Dependent Dirichlet Process Mixtures stat.ML · 2012 · author #2
- A Non-Parametric Bayesian Method for Inferring Hidden Causes cs.LG · 2012 · author #1
- Inference in Hidden Markov Models with Explicit State Duration Distributions stat.ML · 2012 · author #3
Mentions
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Frequent Coauthors
- Tom Rainforth 13 shared papers
- Brooks Paige 11 shared papers
- Jan-Willem van de Meent 10 shared papers
- Hongseok Yang 9 shared papers
- Tuan Anh Le 8 shared papers
- David Tolpin 5 shared papers
- Atilim Gunes Baydin 4 shared papers
- Jan Willem van de Meent 4 shared papers
- Yee Whye Teh 4 shared papers
- Andrew Warrington 3 shared papers
- Maximilian Igl 3 shared papers
- N. Siddharth 3 shared papers
- Robert Cornish 3 shared papers
- Yuan Zhou 3 shared papers
- Alban Desmaison 2 shared papers
- Arnaud Doucet 2 shared papers
- David Martinez Rubio 2 shared papers
- Noah D. Goodman 2 shared papers
- Philip H.S. Torr 2 shared papers
- Pushmeet Kohli 2 shared papers