Frank Wood

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 94

Top Topics

Variational Inference

Image Generation

Reinforcement Learning

Diffusion Models

Top Venues

Publications

Jason Yoo, Dylan Green, Geoff Pleiss, Frank Wood
Online Continual Learning of Video Diffusion Models From a Single Video Stream. CoRR (2024)
Matthew Niedoba, Dylan Green, Saeid Naderiparizi, Vasileios Lioutas, Jonathan Wilder Lavington, Xiaoxuan Liang, Yunpeng Liu, Ke Zhang, Setareh Dabiri, Adam Scibior, Berend Zwartsenberg, Frank Wood
Nearest Neighbour Score Estimators for Diffusion Generative Models. CoRR (2024)
Dylan Green, William Harvey, Saeid Naderiparizi, Matthew Niedoba, Yunpeng Liu, Xiaoxuan Liang, Jonathan Wilder Lavington, Ke Zhang, Vasileios Lioutas, Setareh Dabiri, Adam Scibior, Berend Zwartsenberg, Frank Wood
Semantically Consistent Video Inpainting with Conditional Diffusion Models. CoRR (2024)
Ryan Fayyazi, Christian Weilbach, Frank Wood
Prospective Messaging: Learning in Networks with Communication Delays. CoRR (2024)
Laura Manduchi, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin
On the Challenges and Opportunities in Generative AI. CoRR (2024)
Manuel Glöckler, Michael Deistler, Christian Weilbach, Frank Wood, Jakob H. Macke
All-in-one simulation-based inference. CoRR (2024)
Jonathan Wilder Lavington, Ke Zhang, Vasileios Lioutas, Matthew Niedoba, Yunpeng Liu, Dylan Green, Saeid Naderiparizi, Xiaoxuan Liang, Setareh Dabiri, Adam Scibior, Berend Zwartsenberg, Frank Wood
TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters. CoRR (2024)
Jason Yoo, Yunpeng Liu, Frank Wood, Geoff Pleiss
Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning. CoRR (2024)
Vasileios Lioutas, Jonathan Wilder Lavington, Justice Sefas, Matthew Niedoba, Yunpeng Liu, Berend Zwartsenberg, Setareh Dabiri, Frank Wood, Adam Scibior
Critic Sequential Monte Carlo. ICLR (2023)
Berend Zwartsenberg, Adam Scibior, Matthew Niedoba, Vasileios Lioutas, Justice Sefas, Yunpeng Liu, Setareh Dabiri, Jonathan Wilder Lavington, Trevor Campbell, Frank Wood
Conditional Permutation Invariant Flows. Trans. Mach. Learn. Res. 2023 (2023)
Matthew Niedoba, Jonathan Wilder Lavington, Yunpeng Liu, Vasileios Lioutas, Justice Sefas, Xiaoxuan Liang, Dylan Green, Setareh Dabiri, Berend Zwartsenberg, Adam Scibior, Frank Wood
A Diffusion-Model of Joint Interactive Navigation. NeurIPS (2023)
Yunpeng Liu, Vasileios Lioutas, Jonathan Wilder Lavington, Matthew Niedoba, Justice Sefas, Setareh Dabiri, Dylan Green, Xiaoxuan Liang, Berend Zwartsenberg, Adam Scibior, Frank Wood
Video Killed the HD-Map: Predicting Multi-Agent Behavior Directly From Aerial Images. ITSC (2023)
Andreas Munk, Alexander Mead, Frank Wood
Uncertain Evidence in Probabilistic Models and Stochastic Simulators. ICML (2023)
Saeid Naderiparizi, Xiaoxuan Liang, Berend Zwartsenberg, Frank Wood
Don't be so negative! Score-based Generative Modeling with Oracle-assisted Guidance. CoRR (2023)
Matthew Niedoba, Jonathan Wilder Lavington, Yunpeng Liu, Vasileios Lioutas, Justice Sefas, Xiaoxuan Liang, Dylan Green, Setareh Dabiri, Berend Zwartsenberg, Adam Scibior, Frank Wood
A Diffusion-Model of Joint Interactive Navigation. CoRR (2023)
Yunpeng Liu, Vasileios Lioutas, Jonathan Wilder Lavington, Matthew Niedoba, Justice Sefas, Setareh Dabiri, Dylan Green, Xiaoxuan Liang, Berend Zwartsenberg, Adam Scibior, Frank Wood
Video Killed the HD-Map: Predicting Driving Behavior Directly From Drone Images. CoRR (2023)
Christian Dietrich Weilbach, William Harvey, Frank Wood
Graphically Structured Diffusion Models. ICML (2023)
William Harvey, Frank Wood
Visual Chain-of-Thought Diffusion Models. CoRR (2023)
Setareh Dabiri, Vasileios Lioutas, Berend Zwartsenberg, Yunpeng Liu, Matthew Niedoba, Xiaoxuan Liang, Dylan Green, Justice Sefas, Jonathan Wilder Lavington, Frank Wood, Adam Scibior
Realistically distributing object placements in synthetic training data improves the performance of vision-based object detection models. CoRR (2023)
Atilim Günes Baydin, Barak A. Pearlmutter, Don Syme, Frank Wood, Philip H. S. Torr
Gradients without Backpropagation. CoRR (2022)
William Harvey, Andreas Munk, Atilim Günes Baydin, Alexander Bergholm, Frank Wood
Attention for Inference Compilation. SIMULTECH (2022)
Vasileios Lioutas, Adam Scibior, Frank Wood
TITRATED: Learned Human Driving Behavior without Infractions via Amortized Inference. Trans. Mach. Learn. Res. 2022 (2022)
Jinsoo Yoo, Frank Wood
BayesPCN: A Continually Learnable Predictive Coding Associative Memory. NeurIPS (2022)
Yunpeng Liu, Jonathan Wilder Lavington, Adam Scibior, Frank Wood
Vehicle Type Specific Waypoint Generation. CoRR (2022)
Vasileios Lioutas, Jonathan Wilder Lavington, Justice Sefas, Matthew Niedoba, Yunpeng Liu, Berend Zwartsenberg, Setareh Dabiri, Frank Wood, Adam Scibior
Critic Sequential Monte Carlo. CoRR (2022)
William Harvey, Michael Teng, Frank Wood
Near-Optimal Glimpse Sequences for Improved Hard Attention Neural Network Training. IJCNN (2022)
Peyman Bateni, Jarred Barber, Jan-Willem van de Meent, Frank Wood
Enhancing Few-Shot Image Classification with Unlabelled Examples. WACV (2022)
Andreas Munk, Alexander Mead, Frank Wood
Uncertain Evidence in Probabilistic Models and Stochastic Simulators. CoRR (2022)
William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, Frank Wood
Flexible Diffusion Modeling of Long Videos. NeurIPS (2022)
Berend Zwartsenberg, Adam Scibior, Matthew Niedoba, Vasileios Lioutas, Yunpeng Liu, Justice Sefas, Setareh Dabiri, Jonathan Wilder Lavington, Trevor Campbell, Frank Wood
Conditional Permutation Invariant Flows. CoRR (2022)
Christian Weilbach, William Harvey, Frank Wood
Graphically Structured Diffusion Models. CoRR (2022)
Michael Teng, Michiel van de Panne, Frank Wood
Exploration with Multi-Sample Target Values for Distributional Reinforcement Learning. CoRR (2022)
Jason Yoo, Frank Wood
BayesPCN: A Continually Learnable Predictive Coding Associative Memory. CoRR (2022)
William Harvey, Saeid Naderiparizi, Frank Wood
Conditional Image Generation by Conditioning Variational Auto-Encoders. ICLR (2022)
Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Gunes Baydin, Bradley J. Gram-Hansen, Christian A. Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood
Amortized Rejection Sampling in Universal Probabilistic Programming. AISTATS (2022)
Andreas Munk, Berend Zwartsenberg, Adam Scibior, Atilim Günes Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood
Probabilistic surrogate networks for simulators with unbounded randomness. UAI (2022)
Peyman Bateni, Jarred Barber, Raghav Goyal, Vaden Masrani, Jan-Willem van de Meent, Leonid Sigal, Frank Wood
Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning. CoRR (2022)
William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, Frank Wood
Flexible Diffusion Modeling of Long Videos. CoRR (2022)
Yunpeng Liu, Jonathan Wilder Lavington, Adam Scibior, Frank Wood
Vehicle Type Specific Waypoint Generation. IROS (2022)
William Harvey, Saeid Naderiparizi, Frank Wood
Image Completion via Inference in Deep Generative Models. CoRR (2021)
Andreas Munk, William Harvey, Frank Wood
Assisting the Adversary to Improve GAN Training. IJCNN (2021)
Adam Scibior, Vasileios Lioutas, Daniele Reda, Peyman Bateni, Frank Wood
Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulation. CoRR (2021)
Adam Scibior, Vaden Masrani, Frank Wood
Differentiable Particle Filtering without Modifying the Forward Pass. CoRR (2021)
Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood
q-Paths: Generalizing the Geometric Annealing Path using Power Means. CoRR (2021)
Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood
q-Paths: Generalizing the geometric annealing path using power means. UAI (2021)
Adam Scibior, Vasileios Lioutas, Daniele Reda, Peyman Bateni, Frank Wood
Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulation. ITSC (2021)
Andrew Warrington, Jonathan Wilder Lavington, Adam Scibior, Mark Schmidt, Frank Wood
Robust Asymmetric Learning in POMDPs. ICML (2021)
Boyan Beronov, Christian Weilbach, Frank Wood, Trevor Campbell
Sequential core-set Monte Carlo. UAI (2021)
Frank Wood, Andrew Warrington, Saeid Naderiparizi, Christian Weilbach, Vaden Masrani, William Harvey, Adam Scibior, Boyan Beronov, John Grefenstette, Duncan Campbell, Seyed Ali Nasseri
Planning as Inference in Epidemiological Dynamics Models. Frontiers Artif. Intell. 4 (2021)
Rob Brekelmans, Vaden Masrani, Thang Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen
Annealed Importance Sampling with q-Paths. CoRR (2020)
Andreas Munk, William Harvey, Frank Wood
Assisting the Adversary to Improve GAN Training. CoRR (2020)
Saeid Naderiparizi, Kenny Chiu, Benjamin Bloem-Reddy, Frank Wood
Uncertainty in Neural Processes. CoRR (2020)
Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood
Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective. NeurIPS (2020)
Michael Teng, Tuan Anh Le, Adam Scibior, Frank Wood
Semi-supervised Sequential Generative Models. UAI (2020)
Christian Weilbach, Boyan Beronov, Frank Wood, William Harvey
Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models. AISTATS (2020)
Andrew Warrington, Frank Wood, Saeid Naderiparizi
Coping With Simulators That Don't Always Return. AISTATS (2020)
Andrew Warrington, Saeid Naderiparizi, Frank Wood
Coping With Simulators That Don't Always Return. CoRR (2020)
Frank Wood, Andrew Warrington, Saeid Naderiparizi, Christian Weilbach, Vaden Masrani, William Harvey, Adam Scibior, Boyan Beronov, Ali Nasseri
Planning as Inference in Epidemiological Models. CoRR (2020)
Tom Rainforth, Adam Golinski, Frank Wood, Sheheryar Zaidi
Target-Aware Bayesian Inference: How to Beat Optimal Conventional Estimators. J. Mach. Learn. Res. 21 (2020)
Andrew Warrington, J. Wilder Lavington, Adam Scibior, Mark Schmidt, Frank Wood
Robust Asymmetric Learning in POMDPs. CoRR (2020)
Peyman Bateni, Raghav Goyal, Vaden Masrani, Frank Wood, Leonid Sigal
Improved Few-Shot Visual Classification. CVPR (2020)
Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. CoRR (2020)
Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. ICML (2020)
Peyman Bateni, Jarred Barber, Jan-Willem van de Meent, Frank Wood
Improving Few-Shot Visual Classification with Unlabelled Examples. CoRR (2020)
Jason Yoo, Tony Joseph, Dylan Yung, S. Ali Nasseri, Frank Wood
Ensemble Squared: A Meta AutoML System. CoRR (2020)
Michael Teng, Tuan Anh Le, Adam Scibior, Frank Wood
Semi-supervised Sequential Generative Models. CoRR (2020)
Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood
Gaussian Process Bandit Optimization of theThermodynamic Variational Objective. CoRR (2020)
Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Alexander Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale. CoRR (2019)
William Harvey, Michael Teng, Frank Wood
Near-Optimal Glimpse Sequences for Improved Hard Attention Neural Network Training. CoRR (2019)
Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Alexander Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
Etalumis: bringing probabilistic programming to scientific simulators at scale. SC (2019)
Tuan Anh Le, Adam R. Kosiorek, N. Siddharth, Yee Whye Teh, Frank Wood
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow. UAI (2019)
Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Günes Baydin, Bradley Gram-Hansen, Christian Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood
Amortized Rejection Sampling in Universal Probabilistic Programming. CoRR (2019)
Vaden Masrani, Tuan Anh Le, Frank Wood
The Thermodynamic Variational Objective. CoRR (2019)
Vaden Masrani, Tuan Anh Le, Frank Wood
The Thermodynamic Variational Objective. NeurIPS (2019)
Andrew Warrington, Arthur Spencer, Frank Wood
The Virtual Patch Clamp: Imputing C. elegans Membrane Potentials from Calcium Imaging. CoRR (2019)
Peyman Bateni, Raghav Goyal, Vaden Masrani, Frank Wood, Leonid Sigal
Improved Few-Shot Visual Classification. CoRR (2019)
Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Alexander Heinrich, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley Gram-Hansen, Gilles Louppe, Lawrence Meadows, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. NeurIPS (2019)
Yuan Zhou, Bradley J. Gram-Hansen, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models. CoRR (2019)
William Harvey, Andreas Munk, Atilim Günes Baydin, Alexander Bergholm, Frank Wood
Attention for Inference Compilation. CoRR (2019)
Yuan Zhou, Bradley J. Gram-Hansen, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models. AISTATS (2019)
Adam Golinski, Frank Wood, Tom Rainforth
Amortized Monte Carlo Integration. ICML (2019)
Andreas Munk, Adam Scibior, Atilim Günes Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood
Deep Probabilistic Surrogate Networks for Universal Simulator Approximation. CoRR (2019)
Adam Golinski, Frank Wood, Tom Rainforth
Amortized Monte Carlo Integration. CoRR (2019)
Jan-Willem van de Meent, Brooks Paige, Hongseok Yang, Frank Wood
An Introduction to Probabilistic Programming. CoRR (2018)
Tuan Anh Le, Adam R. Kosiorek, N. Siddharth, Yee Whye Teh, Frank Wood
Revisiting Reweighted Wake-Sleep. CoRR (2018)
Stefan Webb, Adam Golinski, Robert Zinkov, Siddharth Narayanaswamy, Tom Rainforth, Yee Whye Teh, Frank Wood
Faithful Inversion of Generative Models for Effective Amortized Inference. NeurIPS (2018)
Michael Teng, Frank Wood
Bayesian Distributed Stochastic Gradient Descent. NeurIPS (2018)
Tuan Anh Le, Maximilian Igl, Tom Rainforth, Tom Jin, Frank Wood
Auto-Encoding Sequential Monte Carlo. ICLR (Poster) (2018)
Tom Rainforth, Adam R. Kosiorek, Tuan Anh Le, Chris J. Maddison, Maximilian Igl, Frank Wood, Yee Whye Teh
Tighter Variational Bounds are Not Necessarily Better. CoRR (2018)
Maximilian Igl, Luisa M. Zintgraf, Tuan Anh Le, Frank Wood, Shimon Whiteson
Deep Variational Reinforcement Learning for POMDPs. ICML (2018)
Tom Rainforth, Adam R. Kosiorek, Tuan Anh Le, Chris J. Maddison, Maximilian Igl, Frank Wood, Yee Whye Teh
Tighter Variational Bounds are Not Necessarily Better. ICML (2018)
Maximilian Igl, Luisa M. Zintgraf, Tuan Anh Le, Frank Wood, Shimon Whiteson
Deep Variational Reinforcement Learning for POMDPs. CoRR (2018)
Michael Teng, Frank Wood
High Throughput Synchronous Distributed Stochastic Gradient Descent. CoRR (2018)
Atilim Gunes Baydin, Robert Cornish, David Martínez-Rubio, Mark Schmidt, Frank Wood
Online Learning Rate Adaptation with Hypergradient Descent. ICLR (Poster) (2018)
Micha Elsner, Sharon Goldwater, Naomi Feldman, Frank Wood
A Joint Learning Model of Word Segmentation, Lexical Acquisition, and Phonetic Variability. EMNLP (2013)
Ramon Casanova, Ryali Srikanth, Aaron H. Baer, Paul J. Laurienti, Jonathan H. Burdette, Satoru Hayasaka, Lynn Flowers, Frank Wood, Joseph A. Maldjian
Biological parametric mapping: A statistical toolbox for multimodality brain image analysis. NeuroImage 34 (1) (2007)
Frank Wood, Sharon Goldwater, Michael J. Black
A Non-Parametric Bayesian Approach to Spike Sorting. EMBC (2006)